Swarm intelligence is an emerging area in the field of optimization and researchers have developed various algorithms by modeling the behaviors of different swarm of animals and insects such as ants, termites, bees, birds, fishes. In 1990s, Ant Colony Optimization based on ant swarm and Particle Swarm Optimization based on bird flocks and fish schools have been introduced and they have been applied to solve optimization problems in various areas within a time of two decade. However, the intelligent behaviors of bee swarm have inspired the researchers especially during the last decade to develop new algorithms. This work presents a survey of the algorithms described based on the intelligence in bee swarms and their applications.

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A survey: algorithms simulating bee swarm intelligence

In infrastructure management, multi-criteria decision-making (MCDM) has emerged as a decision support tool to integrate various technical information and stakeholder values. Different MCDM techniques and tools have been developed. This paper presents a comprehensive review on the application of MCDM literature in the field of infrastructure management. Approximately 300 published papers were identified that report MCDM applications in the field of infrastructure management during 1980–2012. The reviewed papers are classified into application to the type of infrastructure (e.g. bridges and pipes), and prevalent decision or intervention (e.g. repair and rehabilitate). In addition, the papers were also classified according to MCDM methods used in the analysis. The paper provides taxonomy of those articles and identifies trends and new developments in MCDM methods. The results suggest that there is a significant growth in MCDM applications in infrastructure management applications of MCDM over the last decade...

A review of multi-criteria decision-making methods for infrastructure management

Multi-Criteria Decision Analysis (MCDA) methods are widely used in various fields and disciplines. While most of the research has been focused on the development and improvement of new MCDA methods, relatively limited attention has been paid to their appropriate selection for the given decision problem. Their improper application decreases the quality of recommendations, as different MCDA methods deliver inconsistent results. The current paper presents a methodological and practical framework for selecting suitable MCDA methods for a particular decision situation. A set of 56 available MCDA methods was analysed and, based on that, a hierarchical set of methods' characteristics and the rule base were obtained. This analysis, rules and modelling of the uncertainty in the decision problem description allowed to build a framework supporting the selection of a MCDA method for a given decision-making situation. The practical studies indicate consistency between the methods recommended with the proposed approach and those used by the experts in reference cases. The results of the research also showed that the proposed approach can be used as a general framework for selecting an appropriate MCDA method for a given area of decision support, even in cases of data gaps in the decision-making problem description. The proposed framework was implemented within a web platform available for public use at www.mcda.it.

Generalised framework for multi-criteria method selection

City logistics (CL) tends to increase efficiency and mitigate the negative effects of logistics processes and activities and at the same time to support the sustainable development of urban areas. Accordingly, various measures and initiatives are applying and various conceptual solutions are defining. The effects vary depending on the characteristics of the city. This paper proposes a framework for the selection of the CL concept which would be most appropriate for different participants, stakeholders, and which would comply with attributes of the surroundings. CL participants have different, usually conflicting goals and interests, so it is necessary to define a large number of criteria for concepts evaluation. On the other hand, the importance of the criteria is dependent on the specific situation, i.e., a large number of factors describing the surroundings. In situations like this, selecting the best alternative is a complex multi-criteria decision-making (MCDM) problem consisting of conflicting and uncertain elements. A novel hybrid MCDM model that combines fuzzy Decision Making Trial and Evaluation Laboratory Model (DEMATEL), fuzzy Analytical Network Process (ANP) and fuzzy Visekriterijumska Optimizacija i kompromisno Resenje (VIKOR) methods is developed in this paper. The model provides support to decision makers (planners, city administration, logistics service providers, users, etc.) when selecting the CL concept, which is successfully performed in this paper for the City of Belgrade.

A novel hybrid MCDM model based on fuzzy DEMATEL, fuzzy ANP and fuzzy VIKOR for city logistics concept selection

We study the problem of freight transportation in railway networks, where both passenger and freight trains are run. While the passenger trains have a prescribed timetable that cannot be changed, freight train operators send the infrastructure manager requests to insert new freight trains. For each freight train, the associated train operator specifies a preferred ideal timetable , which can be modified by the infrastructure manager in order to respect safeness operational constraints. In particular, this modification may correspond to routing the train along a path which is different with respect to the one in the ideal timetable. Roughly speaking, the objective is to introduce as many new freight trains as possible by assigning them timetables that are as close as possible to the ideal ones. For this timetabling problem on a generic railway network, we present an integer linear programming formulation, that generalizes some formulations already presented for the case of a single railway line, and a Lagrangian heuristic based on this formulation. Computational results on real-world instances are reported.

Scheduling extra freight trains on railway networks

The paper presents a methodological overview of the application of Multiple Criteria Decision Making/Aiding (MCDM/A) in public transportation. It explains why MCDM/A methodology is so important while dealing with different categories of decision problems that arise in mass transit systems. Major features and basic notions of MCDM/A methodology are presented. Different categories of MCDM/A methods are characterized and classified. Two case studies demonstrate possible applications of MCDM/A methodology in public transportation. In the first case study multiple objective evaluation of the mass transit system developments' scenarios is carried out. Four variants of the mass transit system are evaluated by a consistent family of criteria with an application of ELECTRE III method. The second case study refers to optimization of the crew size in the mass transit system operated by a public transportation company (PTC). Multiple objective mathematical programing problem is formulated and solved by a combination of an original, customized heuristic procedure implemented in a computer software PEOPLE and the Light Beam Search (LBS) method.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/atr.108

The Methodology of Multiple Criteria Decision Making/Aiding in Public Transportation

A fleet sizing problem (FSP) in a road freight transportation company with heterogeneous fleet and its own technical back-up facilities is considered in the paper. The mathematical model of the decision problem is formulated in terms of multiple objective mathematical programming based on queuing theory. Technical and economical criteria as well as interests of different stakeholders are taken into account in the problem formulation. The solution procedure is composed of two steps. In the first one a sample of Pareto-optimal solutions is generated by an original program called MEGROS. In the second step this set is reviewed and evaluated, according to the Decision Maker's (DM's) model of preferences. The evaluation of solutions is carried out with an application of an interactive multiple criteria analysis method, called Light Beam Search (LBS). Finally, the DM selects the most desirable, compromise solution.

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Multiple objective optimization of the fleet sizing problem for road freight transportation

Advanced OR and AI methods in transportation

Planning of an integrated urban transportation system based on macro - simulation and MCDM/A methods

A vehicle assignment problem (VAP) in a road, long-haul, passenger transport company with a heterogeneous fleet of buses is considered in the paper. The mathematical model of the VAP is formulated in terms of multiobjective, combinatorial optimization. It has a strategic, long-term character and takes into account 4 criteria that represent interests of both passengers and the company's management. The decision consists in the definition of weekly operating frequency (number of rides/week) of buses on international routes between Polish and Western European cities. The VAP is solved in a step-wise procedure. In the first step a sample of efficient (Pareto-optimal) solutions is generated using an original metaheuristic method called Pareto Memetic Algorithm. In the second step this sample is reviewed and evaluated by the Decision Maker (DM). In this phase an interactive, multiple criteria analysis method with graphical facilities, called Light Beam Search, is applied. The method helps the DM to define his/her preferences, direct the search process and select the most satisfactory solution.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/atr.5670430207

Jacek Zak

Papers

The Methodology of Multiple Criteria Decision Making/Aiding in Public Transportation

Multiple objective optimization of the fleet sizing problem for road freight transportation

Advanced OR and AI methods in transportation

Planning of an integrated urban transportation system based on macro - simulation and MCDM/A methods

Multiple Criteria Optimization Method for the Vehicle Assignment Problem in a Bus Transportation Company