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Showing papers on "Fleet management published in 2017"


Proceedings ArticleDOI
01 Oct 2017
TL;DR: A reinforcement learning approach which adopts a deep Q network and adaptively moves idle vehicles to regain balance is proposed which is effective under various demand scenarios and will benefit both travelers and operators if implemented in shared mobility-on-demand systems.
Abstract: Shared mobility-on-demand systems have very promising prospects in making urban transportation efficient and affordable. However, due to operational challenges among others, many mobility applications still remain niche products. This paper addresses rebalancing needs that are critical for effective fleet management in order to offset the inevitable imbalance of vehicle supply and travel demand. Specifically, we propose a reinforcement learning approach which adopts a deep Q network and adaptively moves idle vehicles to regain balance. This innovative model-free approach takes a very different perspective from the state-of-the-art network-based methods and is able to cope with large-scale shared systems in real time with partial or full data availability. We apply this approach to an agent-based simulator and test it on a London case study. Results show that, the proposed method outperforms the local anticipatory method by reducing the fleet size by 14% while inducing little extra vehicle distance traveled. The performance is close to the optimal solution yet the computational speed is 2.5 times faster. Collectively, the paper concludes that the proposed rebalancing approach is effective under various demand scenarios and will benefit both travelers and operators if implemented in shared mobility-on-demand systems.

110 citations


Journal ArticleDOI
TL;DR: In this article, a green inventory routing problem with a heterogeneous fleet is introduced, where a comprehensive objective is proposed to minimize the sum of inventory cost and routing cost, where the latter includes driver wage, vehicle fixed cost, fuel and emission costs, in which fuel consumption and emissions are determined by load, distance, speed and vehicle characteristics.
Abstract: This paper introduces a green inventory routing problem with a heterogeneous fleet which extends the conventional inventory routing problem by considering environmental impacts and heterogeneous vehicles. A comprehensive objective is proposed, which minimizes the sum of inventory cost and routing cost, where the latter includes driver wage, vehicle fixed cost, fuel and emission costs, in which fuel consumption and emissions are determined by load, distance, speed and vehicle characteristics. We first construct a mixed-integer program, and then conduct numerical tests to quantify the benefits of using a comprehensive objective and heterogeneous vehicles. Managerial insights are also drawn from parameter analyses.

74 citations


Journal ArticleDOI
TL;DR: In this article, the authors present, define and structure the car rental fleet management problem, which includes operational fleet management issues and problems traditionally studied under the revenue management framework, and identify research directions for the future development of the field.
Abstract: This paper aims to present, define and structure the car rental fleet management problem, which includes operational fleet management issues and problems traditionally studied under the revenue management framework. The car rental business has challenging and distinctive characteristics, which are mainly related with fleet and decision-making flexibility, and that render this problem relevant for academic research and practical applications. Three main contributions are presented: an in-depth literature review and discussion on car rental fleet and revenue management issues, a novel integrating conceptual framework for this problem, and the identification of research directions for the future development of the field.

68 citations


Journal ArticleDOI
TL;DR: The designs and development of a wireless on-board diagnostic system (OBD II) fleet management system that aims to measure speed, distance, and fuel consumption of vehicles for tracking and analysis purposes are described.
Abstract: This paper describes the work that has been done in the design and development of a wireless on-board diagnostic system (OBD II) fleet management system. The system aims to measure speed, distance, and fuel consumption of vehicles for tracking and analysis purposes. An OBD II reader is designed to measure speed and mass air flow, from which the distance and fuel consumption are also computed. This data is then transmitted via WiFi to a remote server. The system also implements global positioning system tracking to determine the location of the vehicle. A database management system is implemented at the remote server for the storage and management of transmitted data and a graphical user interface is developed for analysing the transmitted data. Various qualification tests are conducted to verify the functionality of the system. The results demonstrate that the system is capable of reading the various parameters, and can successfully process, transmit, and display the readings.

67 citations


Journal ArticleDOI
TL;DR: In this article, the authors compare the environmental, social and economic impact of BEVs and diesel delivery vans, providing useful insights to policy makers and fleet owners willing to replace or select delivery vans to include in their city-logistics fleets.
Abstract: Poor air quality in urban areas and environmental concerns attributable to road transportation are growing and significant problems for governments. Many different options have been proposed to lower emissions, and a critical one is the use of battery electric vehicles (BEVs). Since city-logistics accounts for about 25% of urban mobility emissions, we focus on battery electric and diesel delivery vans. The aim of this paper is to present a holistic view of the problem, comparing the environmental, social and economic impact of BEV and diesel delivery vans, providing useful insights to policy makers and fleet owners willing to replace or select delivery vans to include in their city-logistics fleets. In cities where new BEV vans replace old diesel vans and the electricity mix is relatively clean, CO2 emissions and air pollutants decrease by 93–98% and 85–99%, respectively. If BEVs use electricity coming from coal energy and are compared to new diesel vans, reductions of CO2 emissions and air pollutants are in the order of 12–13% and 0–92%, respectively. Longer battery life and greater annual mileage improve these results and decrease cost differences. Results also reveal that annual emissions benefits of replacing older diesel vans with BEVs are on the same order of magnitude of equivalent annual cost differences. From a strictly business perspective, BEV vans are already economically attractive in some cities with existing incentives; however, for other cities incentives equal to the value of their emissions reduction benefits are needed, but might not be sufficient to justify BEV acquisition.

60 citations


Journal ArticleDOI
TL;DR: In this paper, the status of Swedish public bus fleets towards decarbonization, and explore factors affecting regional performance variations and fuel choices are analyzed nationally and regionally through a survey and interviews with experts working with strategic planning at Public Transport Authorities.

59 citations


Proceedings ArticleDOI
01 May 2017
TL;DR: In this paper, a predictive positioning method is presented for improving customer quality of service (QoS) by identifying key locations to position the fleet in order to minimize expected customer wait time.
Abstract: Autonomous Mobility On Demand (MOD) systems can utilize fleet management strategies in order to provide a high customer quality of service (QoS). Previous works on autonomous MOD systems have developed methods for rebalancing single capacity vehicles, where QoS is maintained through large fleet sizing. This work focuses on MOD systems utilizing a small number of vehicles, such as those found on a campus, where additional vehicles cannot be introduced as demand for rides increases. A predictive positioning method is presented for improving customer QoS by identifying key locations to position the fleet in order to minimize expected customer wait time. Ridesharing is introduced as a means for improving customer QoS as arrival rates increase. However, with ridesharing perceived QoS is dependent on an often unknown customer preference. To address this challenge, a customer ratings model, which learns customer preference from a 5-star rating, is developed and incorporated directly into a ridesharing algorithm. The predictive positioning and ridesharing methods are applied to simulation of a real-world campus MOD system. A combined predictive positioning and ridesharing approach is shown to reduce customer service times by up to 29%. and the customer ratings model is shown to provide the best overall MOD fleet management performance over a range of customer preferences.

58 citations


Journal ArticleDOI
TL;DR: In this paper, an agent-based model is developed to estimate the potential future market shares of EVs considering the existing inherent uncertainties under different policy scenarios, including the footprint-based CAFE regulation.

53 citations


Proceedings ArticleDOI
01 Sep 2017
TL;DR: An intelligent patient monitoring system for monitoring the patients' health condition automatically through sensors based connected networks that can able to detect the critical condition of a patient by processing sensors data and instantly provides push notification to doctors/nurses as well as hospital in-charge personal.
Abstract: The popularity of Internet of Things is increasing day by day in the area of remote monitoring system. The remote monitoring systems include, vehicle or assets monitoring, kids/pets monitoring, fleet management, parking management, water and oil leakage, energy grid monitoring etc. In this paper, we have proposed an intelligent patient monitoring system for monitoring the patients' health condition automatically through sensors based connected networks. Several sensors are used for gathering the biological behaviors of a patient. The meaningful biological information are then forwarded to the IoT cloud. The system is more intelligent that can able to detect the critical condition of a patient by processing sensors data and instantly provides push notification to doctors/nurses as well as hospital in-charge personal. The doctors and nurses get benefited from this system by observing their corresponding patients remotely without visiting in person. Patients' relatives can also get benefited from this system with limited access.

52 citations


Journal ArticleDOI
TL;DR: The alternative-fuel multiple depot vehicle scheduling problem is formally defined and formulated as an integer program, and a branch-and-price algorithm is proposed to solve the problem.
Abstract: Alternative-fuel vehicles are gaining popularity as a mode of transit, and research is being done into how current infrastructure can accommodate them. The problem of vehicle scheduling consists of assigning a fleet of vehicles to service a given set of trips with start and end times. Vehicle scheduling changes when alternative-fuel vehicles are used since the vehicles can carry only a limited amount of fuel and can refuel only at fixed locations. This paper presents the alternative-fuel multiple depot vehicle scheduling problem, a modification of the standard multiple depot vehicle scheduling problem where there is a given set of fueling stations and a fuel capacity for the vehicles. The problem is formally defined and formulated as an integer program, and a branch-and-price algorithm is proposed to solve the problem. A heuristic solution is also presented, and both are tested on randomly generated data and data on the Valley Metro bus network in the Phoenix, Arizona, metropolitan area.

52 citations


Journal ArticleDOI
TL;DR: In this article, a taxonomy for classifying vehicle fleet management problems, across several dimensions, is presented to inform future research on autonomous vehicle (AV) fleets, including vehicle routing, scheduling, and fleet management.
Abstract: This paper presents a taxonomy for classifying vehicle fleet management problems, across several dimensions, to inform future research on autonomous vehicle (AV) fleets. Modeling the AV fleet management problem will bring about new classes of vehicle routing, scheduling, and fleet management problems; nevertheless, the existing literature related to vehicle routing, scheduling, and fleet management is a valuable foundation for future research on the AV fleet management problem. This paper classifies the broadly defined AV fleet management problem by using existing taxonomic categories in the literature; adds additional, or more nuanced, dimensions to existing taxonomic categories; and presents new taxonomic categories to classify specific AV fleet management problems. The broadly defined AV fleet management problem can be classified as a dynamic multivehicle pickup and delivery problem with explicit or implicit time window constraints. Existing studies that fit into this class of fleet management problems...

Journal ArticleDOI
TL;DR: Simulation study provides evidence that the match factor can be used to determine ranges for numbers of different types of trucks in an optimal fleet and reveals differences in production with different heterogeneous fleet types.

Proceedings ArticleDOI
01 Dec 2017
TL;DR: REC, a Real-time Ev Charging scheduling framework for EV taxi fleets, which informs each EV taxi driver at runtime when and where to charge the battery, is developed and Experimental results show that REC is able to address the unpredictability and unbalancing issues existing in current EV taxi fleet systems.
Abstract: Due to the energy security concern, our society is witnessing a surge of EV fleet applications, eg, public EV taxi fleet systems A major issue impeding an even more widespread adoption of EVs is range anxiety, which is due to several factors including limited battery capacity, limited availability of battery charging stations, and long charging time compared to traditional gasoline vehicles By analyzing our accessible real-world EV taxi system-wide datasets, we observe that current EV taxi drivers often suffer from unpredictable, long waiting times at charging stations, due to temporally and spatially unbalanced utilization among charging stations This is mainly because current taxi fleet management system simply rely on taxi drivers to make charging decisions In this paper, In this paper, we develop REC, a Real-time Ev Charging scheduling framework for EV taxi fleets, which informs each EV taxi driver at runtime when and where to charge the battery REC is able to analytically guarantee predictable and tightly bounded waiting times for all EVs in the fleet and temporally/spatially balanced utilization among charging stations, if each driver follows the charging decision made by REC Moreover, REC can further efficiently handle real-life issues, eg, allowing a taxi driver to charge at its preferred charging station while still guaranteeing balanced charging station utilizationWe have extensively evaluated REC using our accessible real-world EV taxi system-wide datasets Experimental results show that REC is able to address the unpredictability and unbalancing issues existing in current EV taxi fleet systems, yielding predictable and tightly bounded waiting times, and equally important, temporally/spatially balanced charging station utilization

Journal ArticleDOI
TL;DR: In this paper, the authors compare the differences between the strategies by conducting a stochastic simulation study based on the data gathered from an actual mine and underline the importance of the global vision in dispatching decisions.
Abstract: One of the key factors in a profitable open-pit mine is the efficiency of the waste disposal system. Using GPS-technology, the truck-dispatching decisions can be made in real-time but the chosen strategy has a crucial role. Therefore, finding the optimal dispatching strategy for truck-shovel operations is extremely important. Dispatching strategies have been reported in the literature, but the comparison of these strategies is still missing. This paper illustrates the differences between the strategies by conducting a stochastic simulation study based on the data gathered from an actual mine. The findings underline the importance of the global vision in dispatching decisions.

Journal ArticleDOI
TL;DR: In this article, a multi-criteria decision-making (MCDM) approach is proposed to achieve optimal green aviation fleet management strategy decisions, which integrates the decision making trial and evaluation laboratory (DEMATEL), analytic network processes (ANP) and zero-one goal programming (ZOGP).

Journal Article
TL;DR: The remote control and autonomous operation of earthmoving equipment are identified as the most underdeveloped and complicated areas, and the missing modules and research directions in these fields are discussed.
Abstract: In the construction industry, the earthmoving sector is among the pioneers in adopting new sensing and information technologies to reduce operation costs, improve productivity, and enhance automation and safety. Fleet tracking and management systems, automated machine guidance and control, and proximity detection devices for accident warning are some examples of emerging products for earthmoving equipment. In addition to the commercial solutions, the research community actively develops and evaluates new systems in this area. This paper aims to critically review the related advances in this field. A three-phase literature review was carried out to investigate the innovations in industrial and academic research communities. Advances in six major industrial companies and a total of 102 related academic papers have been reviewed and discussed. Based on the application area and the function, current research works are divided into four categories: equipment tracking and fleet management, safety management, equipment pose estimation and machine control technology, and remote control and autonomous operation. The underlying technologies and methods used in these systems are discussed in detail. Finally, future research opportunities, based on the identified shortcomings and gaps in knowledge, are highlighted. In particular, the remote control and autonomous operation of earthmoving equipment are identified as the most underdeveloped and complicated areas, and the missing modules and research directions in these fields are discussed.

Journal ArticleDOI
TL;DR: It is shown that in some cases traffic restrictions may actually increase the number of vehicles on the streets, and the benefits of operating a heterogeneous fleet of vehicles are studied.
Abstract: We study the strategic problem of a logistics service provider managing a (possibly heterogeneous) fleet of vehicles to serve a city in the presence of access restrictions. We model the problem as an area partitioning problem in which a rectangular service area has to be divided into sectors, each served by a single vehicle. The length of the routes, which depends on the dimension of the sectors and on customer density in the area, is calculated using a continuous approximation. The aim is to partition the area and to determine the type of vehicles to use in order to minimize the sum of ownership or leasing, transportation and labor costs. We formulate the problem as a mixed integer linear problem and as a dynamic program. We develop efficient algorithms to obtain an optimal solution and present some structural properties regarding the optimal partition of the service area and the set of vehicle types to use. We also derive some interesting insights, namely we show that in some cases traffic restrictions may actually increase the number of vehicles on the streets, and we study the benefits of operating a heterogeneous fleet of vehicles.

Proceedings ArticleDOI
01 Sep 2017
TL;DR: A Smart Anti-Theft Vehicle System based on Internet of Things (IoT) for monitoring the movement of any equipped vehicle from anywhere in real time and provides the access to check the movement and control vehicles remotely by using mobile application.
Abstract: With the emergence of new technology and innovations, people are searching smarter ways to protect/monitor their properties remotely. In accordance to that, at present GPS based tracking system is frequently used in vehicle tracking, children/pet tracking, aircraft tracking, any personal belongings tracking, fleet management and so on. This paper introduces a Smart Anti-Theft Vehicle System based on Internet of Things (IoT) for monitoring the movement of any equipped vehicle from anywhere in real time. At the implementation of this system, Global Positioning System (GPS), Global System for Mobile Communication (GSM)/General Packet Radio Service (GPRS) and Microcontrollers are used to enable users for monitoring their vehicles in a convenient manner. This system provides the access to check the movement and control (emergency stop by closing the fuel line) vehicles remotely by using mobile application. The hardware prototype of the proposed system and the user application for monitoring and controlling vehicles are presented in this paper.

Journal ArticleDOI
Ye Li1, Yuewu Yu1
TL;DR: Wang et al. as discussed by the authors investigated how a smart phone freight application service (apps) could reduce CO2 emissions in road freight transport and to identify the core problems for improvements, and then the identification of returning pick-up and route planning was conducted to further improve apps for CO2 reduction.
Abstract: The purpose of this study was to investigate how a smart phone freight application service (Apps) could reduce CO2 emissions in road freight transport and to identify the core problems for improvements. This research uses a multiple-case-study approach to examine several existing freight apps in the Chinese market. The study was conducted using multiple data collection techniques, including interviews, production observation, firsthand experience, and online-search summaries. Inspired by a full analysis of case studies, a hierarchical conceptual framework was developed to provide an overarching view of how existing apps achieve environmental benefits, which deepens our understanding of the interrelationship between freight Apps utilization and CO2 reduction. Freight apps provide a mechanism that auto-match the consignor’s demand and the carrier’s supply based on mobile Internet. The efficient way to find the right truck and complete the delivery process enhances the decrease of truck’s empty travel distances and improvement of average vehicle loaded, then leading to an improvement of efficiency and a decline in carbon emission in freight industry. And then the identification of returning pick-up and route planning was conducted to further improve apps for CO2 reduction. The influences to freight movement system by apps focused on reconstructing the demand and supply with integration technology, and resulted in a more efficient transaction using matching technology and advanced fleet management with optimization technology. When with inter-urban Full Truck Load, freight apps enable carriers to search for demand for returning a pick-up with decreasing empty running mileages, which then has environmental benefits through reducing CO2 emissions. However, when in urban Less-than-Truck Load, by strengthening the average vehicle utilization on laden trips, another determinant of route planning of delivery & collection reduced CO2 emissions. In order to further promote development of apps, in inter-urban Full Truck Load of long-distance transport, sufficient number of users and suitable matching conditions ensured carriers schedule an order to guarantee the return pick-up at an appointed time or grab several orders to achieve a larger non-empty return trip. In this “always-laden” transport plan, consideration should be given to the carriers’ search and waiting costs before starting the next freight service. Meanwhile, route planning of delivery & collection based on real-time traffic information in Less-than-Truck Load required sharing high-level of data, complicated-adaptable models and the efficient computing power. These valuable aspects would be a great challenge for follow-up development of freight apps in aiding CO2 emission reduction.

Proceedings ArticleDOI
17 Aug 2017
TL;DR: In this article, a digital twin of the active engines consisting of multilevel models of the engine and its components is used to support deterioration and failure analysis, predict life consumption of critical parts and relate the specific operation of a customer to the real and expected condition of the engines on-wing and at induction to the shop.
Abstract: Engine operating cost is a major contributor to the direct operating cost of aircraft. Therefore, the minimization of engine operating cost per flight-hour is a key aspect for airlines to operate successfully under challenging market conditions.The interaction between maintenance cost, operating cost, asset value, lease and replacement cost describes the area of conflict in which engine fleets can be optimized.State-of-the-art fleet management is based on advanced diagnostic and prognostic methods on engine and component level to provide optimized long-term removal and work-scoping forecasts on fleet level based on the individual operation. The key element of these methods is a digital twin of the active engines consisting of multilevel models of the engine and its components. This digital twin can be used to support deterioration and failure analysis, predict life consumption of critical parts and relate the specific operation of a customer to the real and expected condition of the engines on-wing and at induction to the shop. The fleet management data is constantly updated based on operational data sent from the engines as well as line maintenance and shop data.The approach is illustrated along the real application on the CFM56-5C, a mature commercial two-spool high bypass engine installed on the Airbus A340-300. It can be shown, that the new methodology results in major improvements on the considered fleets.Copyright © 2017 by ASME

Journal ArticleDOI
TL;DR: A mixed integer program and three heuristics based on Variable Neighborhood Search are presented and it is shown that a subset of options is sufficient to reduce costs remarkable.
Abstract: The problem addressed in this paper extends the vehicle routing problem with private fleet and common carriers by three aspects: two types of rental options, a cost function considering volumes and distances, and volume discounts offered by the common carriers. For its solution, we present a mixed integer program and three heuristics based on Variable Neighborhood Search. The computational analysis demonstrates the suitability of these heuristics and the positive effects of two newly introduced mechanisms. Analyzing the interdependencies between available outsourcing options and economic benefits, it shows that a subset of options is sufficient to reduce costs remarkable.

Journal ArticleDOI
TL;DR: In this article, the existing fleet characteristics in terms of age, annual mileage, fuel economy, fuel type used etc for the freight vehicles used for "interstate" or "intercity" mobility on National Highways Origin-Destination surveys and traffic volume counts are conducted at ten locations along major National Highway to capture the fleet characteristics.

Journal ArticleDOI
TL;DR: In this paper, a hybrid approach was developed through incorporating multi-criteria decision analysis (MCDA) methods within a general life-cycle analysis (LCA) framework to identify and evaluate sustainable strategies of taxi fleet in Beijing in terms of economic, policy, and environmental implications.

Proceedings ArticleDOI
28 Aug 2017
TL;DR: The components of the Traffic-TBD (Traffic Telco Big Data) architecture are outlined, which aims to become an innovative road traffic analytic and prediction system with the following desiderata: provide micro-level traffic modeling and prediction that goes beyond the current state provided by Internet-based navigation enterprises utilizing crowdsourcing.
Abstract: A telecommunication company (telco) is traditionally only perceived as the entity that provides telecommunication services, such as telephony and data communication access to users. However, the IP backbone infrastructure of such entities spanning densely urban spaces and widely rural areas, provides nowadays a unique opportunity to collect immense amounts of mobility data that can provide valuable insights for road traffic management and avoidance. In this paper we outline the components of the Traffic-TBD (Traffic Telco Big Data) architecture, which aims to become an innovative road traffic analytic and prediction system with the following desiderata: i) provide micro-level traffic modeling and prediction that goes beyond the current state provided by Internet-based navigation enterprises utilizing crowdsourcing; ii) retain the location privacy boundaries of users inside their mobile network operator, to avoid the risks of exposing location data to third-party mobile applications; and iii) be available with minimal costs and using existing infrastructure (i.e., cell towers and TBD data streams are readily available inside a telco). Road traffic understanding, management and analytics can minimize the number of road accidents, optimize fuel and energy consumption, avoid unexpected delays, contribute to a macroscopic spatio-temporal understanding of traffic in cities but also to "smart" societies through applications in city planning, public transportation, logistics and fleet management for enterprises, startups and governmental bodies.

Journal ArticleDOI
TL;DR: In this article, a multi-stage stochastic programming model for the bulk ship fleet renewal problem is introduced and solved in a rolling horizon fashion, which outperforms traditional methods relying on expected value forecasts.
Abstract: Faced with simultaneous demand and charter cost uncertainty, an industrial shipping company must determine a suitable fleet size, mix, and deployment strategy to satisfy demand. It acquires vessels by time chartering and voyage chartering. Time chartered vessels are acquired for different durations, a decision made before stochastic parameters are known. Voyage charters are procured for a single voyage after uncertain parameters are realized. We introduce the first multi-stage stochastic programming model for the bulk ship fleet renewal problem and solve it in a rolling horizon fashion. Computational results indicate that our approach outperforms traditional methods relying on expected value forecasts.

Journal ArticleDOI
TL;DR: In this paper, a non-linear arc-based model and an exact solution method based on a set-partitioning formulation are developed to minimize long-term on-shore infrastructure and tanker investment cost combined with interrelated expected cost for operating the tanker fleet.
Abstract: We consider a strategic infrastructure and tanker fleet sizing problem in the liquefied natural gas business. The goal is to minimize long-term on-shore infrastructure and tanker investment cost combined with interrelated expected cost for operating the tanker fleet. A non-linear arc-based model and an exact solution method based on a set-partitioning formulation are developed. The latter approach allows very fast solution times. Computational results for a case study with a liner shipping company are presented, including an extensive sensitivity analysis to account for limited predictability of key parameter values, to analyze the solutions’ robustness and to derive basic decision rules.

Journal ArticleDOI
TL;DR: In this paper, the authors compared the supply costs of a conventional direct forest chip supply to an alternative fuel supply with the use of a feed-in terminal using the discrete-event simulation method.
Abstract: The fuel supply of forest chips has to adapt to the annual fluctuations of power and heat generation. This creates inefficiency and unbalances the capacity utilization of the fuel supply fleet in the direct fuel supplies from roadside storages to power and heat generation. Terminals can offer an alternative approach for the fleet management of fuel supplies in terms of smoothing the unbalanced fleet use towards more even year-round operations. The aim of the study was to compare the supply costs of a conventional direct forest chip supply to an alternative fuel supply with the use of a feed-in terminal using the discrete-event simulation method. The influences of the terminal location, terminal investment cost, outbound terminal transport method, terminal truck utilization and quality changes of terminal-stored forest chips for the fuel supply cost were studied in the case environment. By introducing a feed-in terminal and a shuttle truck for the transports of terminal-stored forest chips, the total supply cost was 1.4% higher than the direct fuel supply scenario. In terminal scenarios, the supply costs increased 1–2% if the cost of the terminal investment increased 30%, the distance to the terminal increased from 5 km to 30 km or the total annual use of a terminal truck decreased 1,500 hours. Moreover, a 1 percent point per month increase in the dry matter loss of terminal-stored chips increased the total supply cost 1%. The study revealed that with the relatively low additional cost, the feed-in terminal can be introduced to the conventional forest chip supply. Cost compensation can be gained through the higher annual use of a fuel supply fleet and more secured fuel supply to power plants by decreasing the need for supplement fuel, which can be more expensive at a time of the highest fuel demand. This article is protected by copyright. All rights reserved.

Journal ArticleDOI
TL;DR: In this article, the effect of transport management on supply chain performance in terms of profitability, reliability, cost, responsiveness, flexibility and asset management efficiency of textile manufacturing firms in Kenya is analyzed.
Abstract: The purpose of the study was to analyze the effect of transport management on supply chain performance in terms of profitability, reliability, cost, responsiveness, flexibility and asset management efficiency of textile manufacturing firms in Kenya. The study was guided by the cooperative game theory. The study adopted the convergent parallel mixed methods design. The study targeted a total of 196 respondents drawn from employees of procurement departments and departmental heads of respective 15 textile manufacturing industries operating in Nairobi County. The sample size was therefore 139 respondents. Stratified and simple random sampling methods were used to select employees of procurement departments from their respective textile firms. Questionnaires and interview schedules were used to gather the data from primary sources. The study applied the use of both qualitative and quantitative data which was analyzed using statistical package for social sciences (SPSS Version 22). Inferential statistics using hierarchical multiple regression and Correlation analysis was applied to test the relationship between the variable and formulated hypothesis. The final analyzed results were presented using tables, graphs and charts. The study concludes that transport management possess the potential of positively influencing supply chain performance of Textile firms and therefore recognizes the importance of transport management in the supply chain. Therefore in order to attain successful organizational performance the study recommends that the management of the textile firms have to put mechanisms in place for addressing transport such as vehicle scheduling, route planning, fleet management, and vehicle tracking for purposes of ensuring competitive edge against other market competitors thus improving superior performance of textile manufacturing firms.

Journal ArticleDOI
TL;DR: A novel pickup policy for courier routing is proposed based on the idea of centrality measures and the nearest-neighbour (NN) policy by considering the un-serviced customer requests as a globally coupled network and significantly outperforms the NN and FCFS policies in terms of waiting time and total service time.
Abstract: As a particular logistics service, the express courier service has seen considerable growth recently, which resulted in an unprecedented fierce competition. Besides, the development of information and communication technologies has enabled express company to manage their service. With the purpose of improving service quality and operation efficiency for express company, we focus on the problem of intercity express courier routing in courier-triggered pickup service. A novel pickup policy for courier routing is proposed based on the idea of centrality measures and the nearest-neighbour (NN) policy by considering the un-serviced customer requests as a globally coupled network. This policy enables to dispatch the idle courier to the more central request location, which allows the courier to easily serve the neighbouring requests around the central request location, thus securing both global and local performance. We also propose a simple prototype of real-time fleet management system where the proposed picku...

Patent
06 Jun 2017
TL;DR: In this article, a fleet management system includes a connected lawn mower, including a prime mover, a mower blade, and a processing circuit including a processor and memory, and the processing circuit receives a cost input indicating an amount of money to complete a job, receives an on-site time for the job, and calculates an efficiency value for the connected mower.
Abstract: A fleet management system includes a connected lawn mower including a prime mover, a mower blade, and a processing circuit including a processor and memory The processing circuit receives a cost input indicating an amount of money to complete a job, receives an on-site time for the job, receives operational data from the connected lawn mower, including a prime mover runtime, calculates an efficiency value for the connected lawn mower based on the prime mover runtime and the on-site time, calculates a profitability value for the job based on at least the cost input and the on-site time, generates an efficiency report and profitability report for the connected unit based on the calculated efficiency and profitability values, and transmits the efficiency report and the profitability report to a computing system