Virus Evolution Strategy for Vehicle Routing Problems with Time Windows

Kanoh, Hitoshi; Tsukahara, Shuichi

doi:10.1007/978-3-540-87700-4_103

Cited by 3 publications

(3 citation statements)

References 9 publications

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“…The results coming from the exact approach will be used in the next section to compare them with those from the heuristic approach in small instance. Based on a very broad field of studies, the genetic algorithm (GA) and Evolutionary Strategy(ES) is promising approximation algorithm that has addressed hard problems in recent decades [9] [10]. For this reason, they will be adopted in the heuristic approach.…”

Section: 1) Exact Approachmentioning

confidence: 99%

“…The results from this experiment are presented in Figure 3. The analysis of the results of the various tests reveals a difference between the quality of the instances ES (10) and ES (40). These negligible differences in quality lead the authors to conclude on the stability of the proposed ES, the accuracy of the parameterization procedure and the effectiveness of the results of the present study.…”

Section: Population Size Experimentsmentioning

confidence: 99%

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Modeling and Optimization of a Multi-Objective Ridesharing Problem in the Case of Medical Waste

2019

IJRTE

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Medical wastes is now a major concern of the world community and more particularly that of Moroccans. Indeed, these wastes, classified as hazardous products, are the source of serious infections, contamination of groundwater and air pollution. Through this paper, we encouraged the use of ridesharing to cope with the risks and costs arising from the logistics of these medical wastes. Thus, we have proposed a mathematical model that governs the multi-objective nature of this logistics and the various constraints associated with it. Since the exact approach had difficulties in large instances, we proposed the Genetic Algorithm and Evolution Strategy as metaheuristic to solve the model. The Evolution Strategy showed its efficiency and stability and therefore we have demonstrated through this metaheuristic the possibility of a compromise between the main objectives of our model.

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Section: 1) Exact Approachmentioning

confidence: 99%

Section: Population Size Experimentsmentioning

confidence: 99%

Modeling and Optimization of a Multi-Objective Ridesharing Problem in the Case of Medical Waste

2019

IJRTE

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“…In this paper, we propose a method of improving the ES in the two-phase method as the computational cost of the first phase is higher than that of the second. The new method introduces a viral infection into the ES [28]. This is called a virus evolutionary strategy (VES) in this paper.…”

Section: Introductionmentioning

confidence: 99%

Solving real-world vehicle routing problems with time windows using virus evolution strategy

Kanoh

Tsukahara

2010

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This paper proposes a new solution to the vehicle routing problem with time windows using an evolution strategy adopting viral infection. The problem belongs to the NP-hard class and is very difficult to solve within practical time limits using systematic optimization techniques. In conventional evolution strategies, a schema with a high degree-of-fitness produced in the process of evolution may not be inherited when the fitness of the individual containing the schema is low. The proposed method preserves the schema as a virus and uses it by the infection operation in successive generations. Experimental results using extended Solomon's benchmark problems with 1000 customers proved that the proposed method is superior to conventional methods in both its rates of searches and the probability of obtaining solutions. Further experiments using the map of the central part of Tokyo with 20000 intersections and real traffic data also gave that the rate of search of the proposed method is higher than that of the conventional method.

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