Showing papers in "International Journal of Operational Research in 2011"
TL;DR: In this paper, a two-level supply chain situation is considered, where a manufacturer/vendor is assumed to receive raw material parts from a number of suppliers for assembling a single product.
Abstract: In this paper, a two-level supply chain situation is considered. A manufacturer/vendor is assumed to receive raw material parts from a number of suppliers for assembling a single product. The parts obtained from the supplier are not of a perfect quality. That is, each supplier may have an approximately fixed percentage of defectives in the lots supplied. An inspection process is carried out at the vendor’s end to take out these imperfect parts while manufacturing the product. A different percentage of defectives from each supplier gives rise to some unused parts left with the vendor in each cycle. These parts are utilised in the next cycle. Different coordination mechanisms for controlling the supply chain inventory are studied. A cost minimisation model is given for each. A numerical example is given to compare the coordination mechanisms.
30 citations
TL;DR: The reliability and availability are considered for four series configurations with both warm and cold standby with the existence of common cause failure of the system at all states with mean time to failure (MTTF) and steady state availability.
Abstract: The reliability and availability are considered for four series configurations with both warm and cold standby with the existence of common cause failure of the system at all states. The mean time to failure (MTTF) and steady state availability are derived for all configurations. It is assumed that the time between failures and repair time to be exponentially distributed. Examples are presented for comparing all configurations for specific values of the different parameters under various costs of the components. The configurations are ranked based on preference with respect to different parameter ratios.
29 citations
TL;DR: In this article, the authors used data envelopment analysis (DEA) models to analyse the relative efficiency and productivity change in Indian pharmaceutical industry (IPI) between 1998 and 2007 which covers the post-TRIPS (1995) and post Indian Patent Act Amendment (2005) period.
Abstract: In this paper, we have used data envelopment analysis (DEA) models to analyse the relative efficiency and productivity change in Indian pharmaceutical industry (IPI) between 1998 and 2007 which covers the post-TRIPS (1995) and post Indian Patent Act Amendment (2005) period. BCC DEA model and Malmquist productivity index are used to estimate the relative efficiency and productivity change of Indian pharmaceutical companies over the 10 year period. We have proposed and tested several hypotheses on the average efficiency and the productivity change of IPI to check if the indigenous and multinational companies differ in their efficiency and productivity change over the aforementioned period. Also, we have analysed the effect of firm size on several performance measures. Exploring the relationship between DEA efficiency and innovation, we find that innovative firms with R&D and patents have higher efficiency than non-innovative firms.
29 citations
TL;DR: The possibility to apply different supply chain (SC) design approaches in presence of reverse flows is addressed, analysing the network structure where the considered flows are forward flow exclusively, or forward and reverse flows, or integral closed-loop flows.
Abstract: Design of distribution networks is one of the most critical issues in the management of supply networks. When the supply chain takes into account the whole life of the product (warranty, remanufacturing, recycle, disposal, etc.), the adverse effects on the logistic flow is quite considerable on the structure of the network. For this reason, these aspects should be considered in network design. This paper addresses the possibility to apply different supply chain (SC) design approaches in presence of reverse flows, analysing the network structure where the considered flows are forward flow exclusively, or forward and reverse flows, or integral closed-loop flows. The study also presents an integrated methodology in closed-loop network design, based on mixed-integer programming, considering as inputs the most important driver as fixed and variable costs (installation, transportation, handling, inventory and production), facilities attributes (type, location, capacity and costs), stochastic demand, multi-echelon, multi-product, multi-production, multi-distribution and multi-transportation system. A real industrial application to validate the proposed closed-loop SC design methodology and a comparison between different SC design approaches are presented as a result of this paper.
26 citations
TL;DR: In this paper, a time dependent innovation driven demand model has been introduced in the basic economic order quantity (EOQ) model to calculate the different optimal policies and the proposed model acknowledged relationship between the innovation coefficient and the optimal policies.
Abstract: Inventory control policies for new-product items are highly perceptive to different marketing policies especially for innovation effects at the earlier stage of the product life cycle but unfortunately classical economic order quantity (EOQ) model do not recognises the innovation driven demand model. In this paper, a time dependent innovation driven demand model has been introduced in the basic EOQ model to calculate the different optimal policies. The proposed model acknowledged relationship between the innovation coefficient and the optimal policies. Four hypotheses were framed in this paper based on the numerical exercise that could explain the impact of dynamic pattern of the innovation coefficient on different optimal policies.
21 citations
TL;DR: In this paper, the authors used autoregressive integrated moving average (ARIMA) models to forecast the demand of fresh produce (fruits and vegetables) on a daily basis.
Abstract: This paper presents the application of autoregressive integrated moving average (ARIMA) models to forecast the demand of fresh produce (fruits and vegetables) on a daily basis. Models were built using 25 months sales data of onion from Ahmedabad market in India. Results show that the model can be used to forecast the demand with mean absolute percentage error (MAPE) of 43.14%. This error is within the acceptable limit for fruits and vegetable markets with highly fluctuating demand pattern. The model was validated taking sales data for the same commodity from a different vegetable market. The proposed forecasting model can be used to assist the farmers in determining the volume of daily harvesting for fruits and vegetables.
20 citations
TL;DR: In this article, an economic order quantity (EOQ) inventory problem is discussed over a finite time for deteriorating items with shortages, where the demand rate is of the ramp-type.
Abstract: An economic order quantity (EOQ) inventory problem is discussed over a finite time for deteriorating items with shortages, where the demand rate is of the ramp-type. It is assumed that a constant fraction of the on-hand inventory deteriorates per unit time. The time-value of money and the effects of inflation are taken into account, considering two separate inflation rates: the internal (within the company) and the external (in general economy) inflation rates. The optimality condition for the cost function is analysed and established. The numerical solutions of the model are obtained by considering shortage and no shortage in inventory. Also, we compare this model with infinite time-horizon model. The sensitivity of the parameters involved in the model is also examined. Finally, some concluding remarks are made to highlight the importance of the present work.
19 citations
TL;DR: In this paper, an integrated production inventory model is developed from the perspective of both the manufacturer and the retailer, where the model assumes exponential demand rate, production rate is demand dependent under the inflation, imperfect production process and multiple deliveries.
Abstract: In this research, an integrated production inventory model is developed from the perspective of both the manufacturer and the retailer. The model assumes exponential demand rate, production rate is demand dependent under the inflation, imperfect production process and multiple deliveries. We have assumed that the produced items deteriorates at a constant rate at the producer’s end due to the proper storages conditions, and as the items reaches the retailer’s end follows the Weibull deterioration. Shortages are allowed at the retailer’s part only and the unfulfilled demand is partially backlogged. A numerical example along with sensitivity analysis is given to illustrate the model. Integrated cost policy is compared with the independent decisions made by the manufacturer and the retailer’s and the necessary conclusions are made. Mathematica5.2 is being used to reach the optimal policies.
19 citations
TL;DR: A two-warehouse inventory model under the conditions of permissible delay in payments in fuzzy environment is developed and numerical example is given to illustrate feasibility of the model.
Abstract: In this paper, a two-warehouse inventory model under the conditions of permissible delay in payments in fuzzy environment is developed. A rented warehouse is used when the ordering quantity exceeds the limited capacity of the owned warehouse. During the permissible delay period, no interest is charged by the supplier, but beyond this period interest is charged under the terms and conditions agreed upon and, moreover, interest can be earned on the revenue received during the credit period. Here, we have discussed four different cases to represent realistic situations of market: (1) when the inventory system has both the warehouse facilities, (2) when the owned warehouse has large capacity to store the inventory, (3) when simple EOQ model of single storage system and (4) when one does not wish to take RW services and OW has unlimited capacity. Finally, numerical example is given to illustrate feasibility of the model.
18 citations
TL;DR: An integer programming model and a tabu search heuristic are developed for solving the onerous task of minimising the service disruptions and vehicle operating costs of the Center for Addictive Behavior Health and Recovery Services.
Abstract: In the Center for Addictive Behavior Health and Recovery Services, Inc. (CAB) based in Massachusetts, a dial-a-ride system has been in operation to serve outpatients such as drug and alcohol addicts requesting both delivery and pickup services through telephone calls. As the number of outpatients continues to increase with constrained vehicle capacity and operating budget, CAB copes with the onerous task of minimising the service disruptions and vehicle operating costs. To handle this challenging task, we developed an integer programming model and a tabu search heuristic for solving that model. A series of computational experiments that we made through the real-world problems encountering CAB substantiated the practicality of the proposed model and tabu search heuristic. In addition, the solution quality (accuracy) and computational efficiency of the tabu search heuristic were verified by comparing its test result to those of the branch and bound algorithm.
17 citations
TL;DR: The model contributes to the current literature by relaxing the deterministic demand assumption which has been used for almost all integrated inventory models.
Abstract: In this paper, we consider single vendor-single buyer integrated inventory model with probabilistic demand and equal delivery lot size. The model contributes to the current literature by relaxing the deterministic demand assumption which has been used for almost all integrated inventory models. The objective is to minimise expected total costs incurred by the vendor and the buyer. We develop effective iterative procedures for finding the optimal solution. Numerical examples are used to illustrate the benefit of integration. A sensitivity analysis is performed to explore the effect of key
TL;DR: In this article, a new slack DEA model is proposed which extends the radial efficiency measure with the actual impact of slacks on efficiency scores, and the model satisfies monotone decreasing property with respect to slacks.
Abstract: The total potentials for improvement frequently remain unrevealed by calculating radial efficiency measure by basic data envelopment analysis (DEA) models. In this paper, we propose a new slack DEA model which extends the radial measure with the actual impact of slacks on efficiency scores. The new slack model (NSM) deals directly with input and output slacks. The model satisfies monotone decreasing property with respect to slacks. It also satisfies all other properties of radial DEA model, such as unit invariance and translation invariance, in outputs for the input-oriented model. The dual of this model reveals that all multipliers have become positive, i.e. all input and output variables are fully utilised in the performance assessment of the decision-making units. The study describes the characterisation of the NSM theoretically and empirically by numerical example. For this purpose, we measure the efficiency of the 15 regions of Uttar Pradesh State Road Transport Corporation for the year 2004?2005 through new slack DEA model.
TL;DR: The results show that a firm manufacturing strategy should consider know-how and customer focus on their manufacturing capability transformation to get information related to product life cycle and costs of technology and opportunity lost.
Abstract: This paper focuses on reconfiguring manufacturing capabilities by aligning know-how and customer focus capabilities in finding manufacturing capabilities mechanism. The methodology applies Newsboy problem to capability transformation and game theory to capture bigger market share. Further, response analysis finds reconfiguration response pattern. The results show that a firm manufacturing strategy should consider know-how and customer focus on their manufacturing capability transformation to get information related to product life cycle and costs of technology and opportunity lost. The proposed approach shows that combination among Newsboy vendor problem, game theory and system dynamic models is suitable to be applied in maintaining the firm competitiveness. An innovated model of 'Newsboy vendor-game theory-system dynamic' shows the novelty of this proposed methodology.
TL;DR: A fuzzy goal programming (FGP) model is developed to solve quadratic bilevel programming problems with fuzzy resource constraints for proper distribution of decision powers to the leader and follower and is converted into an equivalent non-linear FGP model to achieve the highest degree of satisfaction to the extent possible.
Abstract: In this paper, a fuzzy goal programming (FGP) model is developed to solve quadratic bilevel programming problems with fuzzy resource constraints for proper distribution of decision powers to the leader and follower. In the model, formulation of the problem, concept of tolerance membership functions for measuring the degree of satisfaction of the objective of the leader and follower are defined first, under the fuzzily described system constraints. Subsequently, a quadratic programming model is constructed on the basis of degree of satisfaction of both the leader and follower. The developed model is converted into an equivalent non-linear FGP model to achieve the highest degree of satisfaction (unity) to the extent possible. In the decision process, the Taylor’s series approximation technique is applied to linearise the non-linear goals and to achieve the fuzzy goal objective values of the decision-makers at both the levels, by arriving at most satisfactory solution regarding the optimality of two different sets of decision variables controlled separately by each of them. An illustrative example is solved to demonstrate the efficiency of the proposed approach and the solution is compared with the solution obtained by using an existing methodology developed by Osman et al. in 2004.
TL;DR: In this article, an integrated supplier?buyer inventory model is studied when the units in inventory are subject to deterioration at a constant rate, the market demand is quadratic and sensitive to retailer price and the supplier offers a trade credit.
Abstract: In this paper, an integrated supplier?buyer inventory model is studied when the units in inventory are subject to deterioration at a constant rate, the market demand is quadratic and sensitive to retailer price and the supplier offers a trade credit. The trade credit policy under assumption is 'two-part' strategy viz. 'net credit', that is, retailer has a choice between cash discount and trade credit. 'Net credit' means if the buyer pays within time period M1 then the buyer receives a cash discount; otherwise, the full account must be settled before time period M2 where M2 > M1 ≫ 0. The goal is to determine the optimal pricing, ordering, shipping and payment policy to maximise the joint profit per unit time. An algorithm is given to obtain optimal solution. The numerical example is given to validate the proposed model and to arrive at managerial insights.
TL;DR: A model that reallocates hospital capacities taking into account the effect of casualty severity on medical care demands and travel time to hospitals on casualty outcomes is developed and an algorithm that dynamically updates the pre-disasters plans to post-disaster reality is developed.
Abstract: This research presents significant improvements to the hospital capacity planning models for hurricane disaster proposed by Paul and Batta. Firstly, we develop a model that reallocates hospital capacities taking into account the effect of casualty severity on medical care demands and travel time to hospitals on casualty outcomes. Secondly, travel time to hospitals, a key input to the model, is estimated using a stochastic simulation. Thirdly, in order to meet with challenges that arise as disaster evolves, we develop an algorithm that dynamically updates the pre-disaster plans to post-disaster reality. The algorithm evaluates prior decisions by dynamically updating the hospital status, travel times and status of the casualty clusters. We demonstrate the application of models in developing pre-disaster plans (hospital capacity and ambulance reallocation) through a case study on New Orleans. In addition, we show the application of the algorithm for post-disaster planning via illustrative examples.
TL;DR: A Markovian model was used to derive a closed form expression for the steady state availability for a system that is allowed to undergo several stages of deteriorations subject to several failures at each state.
Abstract: In this paper, a Markovian model was used to derive a closed form expression for the steady state availability for a system that is allowed to undergo several stages of deteriorations subject to several failures at each state. The failures include random failure, common-cause failure and human error. The system is inspected after each deteriorated state, where one of the two actions is possible, no action or minimal repair which brings the system to the previous deteriorated state. A complete replacement is allowed after n deteriorated states. Moreover, the system is allowed to become as good as new after common-cause or human error failures. The steady state availability is derived for the complete problem, and for three special cases. An example is provided to illustrate the performance of the different cases.
TL;DR: In this article, the authors study a lost-sales ( s, Q ) inventory system with two classes of customers (high priority and low priority) and compare two policies for supplying the two types of customers with their requirements.
Abstract: In this paper, we study a lost-sales ( s , Q ) inventory system with two classes of customers – high priority and low priority. We compare two policies for supplying the two types of customers with their requirements. In one policy, both customers are treated alike. In the other policy, when inventory levels are below a threshold level, only the demands from high-priority (HP) customers are met, whereas the low-priority (LP) customers are sent away unsatisfied. Under certain conditions, we note the remarkable fact that for a lost-sales ( s , Q ) inventory system with two classes of customers, differentiating between customers and hoarding items for the HP customer yield lower costs for the supplier and better service levels for both types of customers.
TL;DR: A mathematical model to identify machine cells and part families simultaneously, so that the number of voids and exceptional elements are minimised is proposed.
Abstract: Cellular manufacturing is an application of group technology (GT) concepts. The aim of a cellular manufacturing system (CMS) is to identify similar manufacturing processes and features where machines are grouped into machine cells based on their contributions to the production process. It has been realised that CMSs benefit from the advantages of both product-based manufacturing systems and job shop manufacturing systems. The cell formation problem (CFP) is one of the key issues in the design of CMS which deals with the identification of machine cells and part families. Many authors adopt either a sequential or a simultaneous procedure to group the parts and machines. The sequential procedure used in some of these studies determines the part families first, followed by machine assignments. On the other hand, the simultaneous procedure determines the part families and machine groups concurrently. This paper proposes a mathematical model to identify machine cells and part families simultaneously, so that the number of voids and exceptional elements are minimised. To evaluate performance of the proposed model, a number of test problems adopted from the literature are solved and the solutions are compared with those of previous well-known methods using the grouping efficacy measure.
TL;DR: In this article, the authors considered a production inventory system with the assumption that the life time of the product is random and follows a Weibull distribution, and derived the optimal production scheduling policies.
Abstract: Production scheduling is an important part of manufacturing. For production scheduling, inventory models play a dominant role. Most of the inventory models of deteriorating items assume that the rate of deterioration is known and constant. In this paper, we concern ourselves with a production inventory system with the assumption that the life time of the product is random and follows a Weibull distribution. The Weibull rate of decay includes increasing, decreasing and constant rates of decay. Assuming that the demand rate is a function of production quantity in a cycle and using the differential equations, the optimal production scheduling policies are derived. The sensitivity of the model with respect to the parameters and cost is also studied. This model is much useful for analysing the production schedules of the seasonal products. It is observed that the decay distribution has an influence on the production schedule.
TL;DR: In this article, a decision-making model for optimisation of operator allocation in a Cellular Manufacturing System (CMS) using computer simulation (CS) and genetic algorithm (GA) is presented.
Abstract: By noting the importance of flexible manufacturing system (FMS), variable market and reduction in product life cycle, this study presents a decision-making model for optimisation of operator allocation in a Cellular Manufacturing System (CMS) using computer simulation (CS) and genetic algorithm (GA). This study determines the number of cross-trained operators and optimum operators’ layout with respect to cellular condition in a CMS by an integrated approach. The main contribution of this paper is utilisation of an integrated CS–GA approach for optimum allocation of operators in a CMS whereas previous studies only use CS or other meta-heuristics. A typical U-shaped CMS is used as the case study to show superiority and advantage of the proposed approach.
TL;DR: A comparison of the performance of the new MRP method with the traditional one shows that the new one takes effectively into account capacity constraints and provides feasible plans.
Abstract: The two main limits of material requirements planning (MRP) systems are: (1) MRP does not take into account production capacity constraints and (2) lead time values are pre-defined input of the procedure. The approaches developed so far solve the first limitation by considering capacity constraints out of the procedure. Target of this paper is to define a new MRP method that overcomes these limitations. In particular, the proposed procedure, through a simulation model, allows to obtain a plan, which complies with resources capacity and which does not need to receive estimated lead time values as input. The proposed method has been applied to a case presenting all the elements of complexity of the MRP phase. A comparison of the performance of the new procedure with the traditional one shows that the new one takes effectively into account capacity constraints and provides feasible plans.
TL;DR: In this article, a mathematical model and a solution methodology for the "carbon market sensitive green supply chain network design" (CMS/GSCND) problem are introduced, where carbon trading is integrated within the supply chain (SC) network design phase and the problem formulated as multiobjective mixed integer linear optimisation program to decide on the SC configuration.
Abstract: Regulatory frameworks to reduce greenhouse gases (GHGs) emissions are currently being developed in many countries around the globe. As a consequence, companies need to consider the different available options and mechanisms to meet their legal obligation. This paper introduces a mathematical model and a solution methodology for the ‘carbon market sensitive green supply chain network design’ (CMS/GSCND) problem. Specifically, carbon trading are integrated within the supply chain (SC) network design phase and the problem formulated as multiobjective mixed integer linear optimisation programme to decide on the SC configuration. The solution methodology allows the economic evaluation of different strategic decisions such as supplier and subcontractor selection, product allocation, capacity utilisation, transportation configuration and their impact in term of carbon footprint. It also provides decision makers with the ability to understand the trade-offs between total logistics costs and GHGs reduction. Model ...
TL;DR: Besides obtaining system length distribution, the model is reinvestigated and the joint distribution of the number of customers in the queue and number with the departing batch at departure-epoch is derived and derived.
Abstract: In a recent paper, Chang et al. (2004) analysed finite-buffer bulk-arrival bulk-service queue with variable server capacity:
TL;DR: The MPSCX is proposed, which generalises the two-parent sequential constructive crossover (SCX) to a multi-parent crossover for the travelling salesman problem (TSP) and the efficiency is compared as against multi- parent partially mapped crossover (MPPMX).
Abstract: Crossover operator plays a vital role in genetic algorithms. This paper proposes the multi-parent sequential constructive crossover (MPSCX), which generalises the two-parent sequential constructive crossover (SCX) to a multi-parent crossover for the travelling salesman problem (TSP). Experimental results on five TSPLIB instances show that MPSCX significantly improves SCX by up to 4.60% in average tour value with maximum 4.01% away from the exact optimal solution. Finally, the efficiency of the MPSCX is compared as against multi-parent partially mapped crossover (MPPMX). Experimental results show that the MPSCX is better than the MPPMX.
TL;DR: The multiplicative analytic hierarchy process (MAHP) as mentioned in this paper has been proposed in response to some perceived shortcomings of the traditional version of the AHP, and the rank reversal issue in the context of MAHP has been investigated.
Abstract: The multiplicative analytic hierarchy process (MAHP) has been proposed in response to some perceived shortcomings of the traditional version of the analytic hierarchy process (AHP). This paper joins a series of articles that investigated the rank reversal issue in the context of MAHP. In general, many of the previous articles did not highlight their interpretation of MAHP properly. In this paper, we consider MAHP as suggested by one of the proponents of the methodology and highlight three important operations that distinguish MAHP from its traditional counterpart. We further discuss three sets of simulation experiments to study the rank reversal properties of MAHP. Results indicate that MAHP possesses desirable rank reversal properties.
TL;DR: The bottleneck travelling salesman problem is to find a Hamiltonian circuit that minimises the maximum arc length in a graph and a data-guided lexisearch algorithm is presented to obtain exact optimal solution.
Abstract: The bottleneck travelling salesman problem is to find a Hamiltonian circuit that minimises the maximum arc length in a graph. We first modify an existing lexisearch algorithm by incorporating good upper and lower bounds to obtain exact optimal solution to the problem. Then we present a data-guided lexisearch algorithm. Depending on the medians of rows of the cost matrix for the problem, the nodes of the network are renamed and a new alphabet table is constructed and then the modified lexisearch algorithm is applied. It is shown that this minor preprocessing of the data, before the lexisearch algorithm is applied, improves computational time substantially. The efficiency of our algorithms as against the existing lexisearch algorithm to the problem has been examined for some TSPLIB (1995) instances and a variety of randomly generated instances of different sizes and different types.
TL;DR: A general framework is proposed for this multi-product, closed-loop system and a non-linear programming (NLP) model is developed to maximise the total expected profit by optimally deciding quantity of parts to be remanufactured and quantity of part to be purchased from external suppliers.
Abstract: This paper considers a supply network consisting of a manufacturer, its external suppliers, and a remanufacturing facility. The manufacturer, facing an uncertain market demand and return, has two options for supplying parts: either ordering the required parts from external suppliers or remanufacturing used products and bringing those back to ‘as good as new’ conditions. We proposed a general framework for this multi-product, closed-loop system and developed a non-linear programming (NLP) model to maximise the total expected profit by optimally deciding quantity of parts to be remanufactured and quantity of parts to be purchased from external suppliers. We solved the mathematical model using GAMS and CONOPT. With a numerical example, we introduced sensitivity analysis to illustrate the interacting effects among critical parameters in the model.
TL;DR: In this article, a modified M-vacation policy and variant arrival rate is considered in a M X / G (a, b )/1 queueing system with modified Mvacations policy.
Abstract: In this paper, a M X / G ( a , b )/1 queueing system with modified M-vacation policy and variant arrival rate is considered. After a service completion, if the number of waiting customers is less than a, then the server avails of multiple vacations till the queue length reaches a or consecutively avail of M number of vacations, whichever occurs first. After completing the Mth vacation, if the queue length is still less than a then the server remains in the system till it reaches a . The server starts the service only if the queue length
TL;DR: A non-linear optimisation model of the resulting generalised crashing problem is formulated, and a convex geometric programming approximation of this model is developed that can be readily extended to handle situations where it is desired to determine the minimum capital investment needed to crash activities.
Abstract: In this paper, we are concerned with the project crashing problem. The functional form we consider for the crashing costs is a negative-exponential form of the amount of capital invested that captures most of the more realistic forms that have been proposed in the literature.We formulate a non-linear optimisation model of the resulting generalised crashing problem, and develop a convex geometric programming approximation of this model. The model can be readily extended to handle situations where it is desired to determine the minimum capital investment needed to crash activities so that the total project duration does not exceed a given time length. Numerical illustrations of the approach are provided.