Network design: selection and design of links and facility location

Drezner, Zvi; Wesolowsky, George O.

doi:10.1016/s0965-8564(02)00014-9

Cited by 76 publications

(65 citation statements)

References 8 publications

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“…Like scatter search, GA is a population-based metaheuristic which was first introduced by Holland (1975). GA has been successfully applied in the network design problems (e.g., Yin, 2000;Drezner and Salhi, 2002;Drezner and Wesolowsky, 2003;Cantarella et al, 2006;Chen et al, 2006).…”

Section: Comparison With Genetic Algorithmmentioning

confidence: 99%

Mixed network design using hybrid scatter search

Khooban¹,

Farahani

Miandoabchi³

et al. 2015

European Journal of Operational Research

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This research proposes a bi-level model for the mixed network design problem (MNDP). The upper level problem involves redesigning the current road links' directions, expanding their capacity, and determining signal settings at intersections to optimize the reserve capacity of the whole system.The lower level problem is the user equilibrium traffic assignment problem. By proving that the optimal arc flow solution of the bi-level problem must exist in the boundary of capacity constraints, an exact line search method called golden section search is embedded in a scatter search method for solving this complicated MNDP. The algorithm is then applied to some real cases and finally, some conclusions are drawn on the model's efficiency.

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Section: Comparison With Genetic Algorithmmentioning

confidence: 99%

Mixed network design using hybrid scatter search

Khooban¹,

Farahani

Miandoabchi³

et al. 2015

European Journal of Operational Research

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“…Researcher and practitioner applied GAs to various facility location and network design problems and proved to be a very effective heuristic method to solve this type of problem, especially problems of large scale (see, e.g. Alp et al, 2003;Drezner & Wesolowsky, 2003;.…”

Section: Priority-based Genetic Algorithmsmentioning

confidence: 99%

Reliable multi period multi product supply chain design with facility disruption

Rafiei¹,

Mohammadi²,

Torabi³

2013

10.5267/j.dsl

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This paper presents a strategic multi segment, multi period and multi-product supply chain management to meet reliable networks for handling disruptions strike. We present a mixedinteger programming model whose objective is to minimize the expected cost composed of probability and cost of occurrence in each scenario. The proposed model of this paper considers time value of money for each operation and transportation cost. We attempt to minimize expected costs by considering the levels of inventory, back-ordering, the available machine capacity and labor levels for each source, transportation capacity at each transshipment node and available warehouse space at each destination. The problem is generalized by taking into account backup supplier with reserved capacity and backup transshipment node that, which satisfies demands at higher price without disruption facility. We use a priority-based genetic algorithms encoding to solve the proposed problem under multi period and multi product conditions. The performance of the proposed model is examined using some instances.

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“…GA has been successfully applied in the network design problems (e.g., Yin 2000Yin , 2002Drezner and Salhi 2002;Drezner and Wesolowsky 2003;Chen et al 2006Chen et al , 2010a. The algorithm proposed here is a multi-objective hybrid version of GA and SA adopted from our previous work (Miandoabchi et al 2010).…”

Section: Multi-objective Hybrid Genetic Algorithmmentioning

confidence: 99%

“…Lane reallocation in streets in peak periods has been considered in Zhang and Gao (2007), and lane allocation and street orientation along with signal timing and parking lane allocation were investigated in . Finally, the combination of street construction and mixed one-way and two-way street configuration was studied in Drezner and Wesolowsky (2003).…”

Section: Introductionmentioning

confidence: 99%

Bi-objective bimodal urban road network design using hybrid metaheuristics

Miandoabchi

Farahani

Szeto

2011

Cent Eur J Oper Res

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In this paper a bimodal discrete urban road network design problem with bus and car modes is investigated. The problem consists of decision making for lane addition to the existing streets, new street constructions, converting some two-way streets to one-way streets, lane allocation for two-way streets, and the allocation of some street lanes for exclusive bus lanes. Two objectives are considered in the problem: maximization of consumer surplus, and maximization of the demand share of the bus mode. The interaction of automobile and bus flows are explicitly taken into account and a modal-split/assignment model is used to obtain the automobile and bus flows in the deterministic user equilibrium state. The main contribution of the paper lies in proposing a new network design problem that combines the road network design decisions with the decision making for bus networks. The problem is formulated as a mathematical program with equilibrium constraints. A hybrid of genetic algorithm and simulated annealing, a hybrid of particle swarm optimization and simulated annealing, and a hybrid of harmony search and simulated annealing are proposed to solve the problem. Computational results for a number of test networks are presented and investigated.Keywords Bimodal network design · Multi-objective · Elastic demand · Hybrid metaheuristics · Exclusive bus lanes

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Network design: selection and design of links and facility location

Cited by 76 publications

References 8 publications

Mixed network design using hybrid scatter search

Mixed network design using hybrid scatter search

Reliable multi period multi product supply chain design with facility disruption

Bi-objective bimodal urban road network design using hybrid metaheuristics

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