Very large street routing problem with mixed transportation mode

Matis, Peter; Koháni, Michal

doi:10.1007/s10100-010-0159-2

Cited by 11 publications

(2 citation statements)

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“…In recent years, there has been an increasing interest in solving UTNDPs by metaheuristic algorithms and especially their hybrid versions (e.g., Drezner and Salhi 2002;Poorzahedy and Rouhani 2007;. The use of metaheuristic algorithms for solving other types of transportation related problems has also been among the subjects of interest (e.g., Reimann and Ulrich 2006;Sörensen 2006;Matis and Koháni 2010). In our previous work (Miandoabchi et al 2010), three hybrid multi-objective metaheuristics were proposed: a hybrid of genetic algorithm and simulated annealing, an evolutionary simulated annealing, and a hybrid of artificial bee colony algorithm and simulated annealing.…”

Section: Solution Procedures For the Problemmentioning

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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Section: Solution Procedures For the Problemmentioning

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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“…The results reported of the applications of TS to sequencing type problems are remarkable and exhibit considerable robustness (Ben‐Daya and Al‐Fawzan, 1998). In this research, since a vehicle routing plan is viewed as a sequence of retail stores and TS has been successfully applied to solve several types of VRP (Kuo et al , 2009; Matis and Koháni, 2010). TS is proposed for optimizing the routing plan.…”

Section: Simple Tabu Searchmentioning

confidence: 99%

Optimizing the VRP by minimizing fuel consumption

Kuo

Wang

2011

Management of Env Quality

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PurposeIn recent years, people have started to realize the importance of environmental protection, and in particular the problem of global warming. Consequently, many governments have started to view decreasing carbon emissions as a priority. Green transportation is one of the policies that is relevant to these efforts. This research aims to optimize the routing plan with minimizing fuel consumption.Design/methodology/approachIn this research, a model is proposed for calculating the total fuel consumption when given a routing plan. Three factors which greatly affect fuel consumption of transportation – transportation distance, transportation speed and loading weight – are taken into consideration. Then a simple Tabu Search is used to optimize the routing plan and an experimental evaluation of the proposed method is performed.FindingsIt is shown that the proposed method provides substantial improvements over a method based on minimizing transportation distances.Originality/valueThe experimental results show that the routing plans found by the proposed method require less fuel consumption than that found by optimizing methods in which the distance travelled was minimized. That means that, if the distribution center can transport goods using vehicles with better fuel consumption, and the drivers can drive in the such a way as to reduce the discharge of carbon, then the proposed method can be a strategy for the continuous improvement of fuel consumption.

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