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6 篇 会议

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检索条件"主题词=Taboo Searching Algorithm"

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Study on Hybrid Heuristic algorithm for Multi-vehicle and Multi-cargo Loading Problem

引用

3rd International Conference on Measuring Technology and Mechatronics Automation (ICMTMA 2011)

作者： Wang, Xiaobo Sun, Jinying Ren, Chunyu Li, Haichen Heilongjiang Univ Sch Informat Management Harbin Peoples R China Building Energy Engn Ctr China Architect Design & Res Grp Beijing Peoples R China

ISBN: (纸本)9783037850190

This paper studies multi-vehicle and multi-cargo loading problem under the limited loading capacity. Hybrid heuristic algorithm is used to get the optimization solution. Firstly, adopt hybrid coding so as to make the problem more succinctly. On the basis of cubage-weight balance algorithm, construct initial solution to improve the feasibility. Adopt the improved non-uniform mutation so as to enhance local search ability of chromosomes. Secondly, stock elite by tabu searching algorithm to improve the searching efficiency of algorithm. Finally, the example can be shown that the algorithm is effective and can provide for large-scale ideas to solve practical problems.

关键词： multi-vehicle and multi-cargo loading problem improved non-uniform mutation stock elite taboo searching algorithm hybrid genetic algorithm

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Study on Hybrid Heuristic algorithm for Vehicle Routing Problem with Backhauls

Study on Hybrid Heuristic Algorithm for Vehicle Routing Prob...

引用

International Conference on Information Technology and Computer Science

作者： Ren Chunyu Sun Jinying Wang xiaobo Heilongjiang Univ Sch Informat Sci & Technol Harbin Peoples R China Building Energy Engn Ctr China Architecture Design & Res Grp China Building Design Consultants Beijing Peoples R China

ISBN: (纸本)9780769536880

In order to satisfy with the individual and various demand of customer, establish vehicle scheduling with backhauls model. According to the characteristics of model, hybrid genetic heuristic algorithm is used to get the optimization solution. First of all, use natural number coding so as to simplify the problem;retain the best selection so as to guard the diversity of group. Improved ordinal crossover operators can avoid destroying good gene parts during the course of ordinal crossover so as that the algorithm can be convergent to the optimization as whole. Secondly, stock elite adopting genetic algorithm take the hybrid genetic algorithm with taboo searching algorithm to improve the convergent speed and searching efficiency of algorithm. The emulation and calculation proves that it is better than only using genetic algorithm and taboo searching algorithm.

关键词： VRPB hybrid genetic algorithm taboo searching algorithm hybrid heuristic algorithm

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Study on Hybrid Genetic algorithm for Hybrid Picking-Delivery Strategy Vehicle Routing Problem

Study on Hybrid Genetic Algorithm for Hybrid Picking-Deliver...

引用

21st Chinese Control and Decision Conference

作者： Ren Chunyu Wang Xiaobo Heilongjiang Univ Sch Informat Sci & Technol Harbin 150080 Peoples R China

ISBN: (纸本)9781424427239

In order to satisfy with the individual and various demand of customer, establish vehicle scheduling with picking-delivery model. According to the characteristics of model, hybrid genetic algorithm is used to get the optimization solution. First of all, use natural number coding so as to simplify the problem;use the individual amount control choice strategy so as to guarantee the diversity of group. Improved ordinal crossover operators can avoid destroying good gene parts during the course of ordinal crossover so as that the algorithm can be convergent to the optimization as whole. The study adopts 2- exchange mutation operator to strengthen the partial searching ability of chromosome. Secondly, stock elite adopting genetic algorithm take the hybrid genetic algorithm with taboo searching algorithm to improve the convergent speed and searching efficiency of algorithm. This algorithm has the characteristics of simple, clear and flexible and it can offer the thought to settle the practical problem in scale. At the same time, it can be known that adopting hybrid picking-delivery strategy can save the distance of distribution route so as to reduce company operating cost and improve economic benefit.

关键词： Vehicle Routing Problem Hybrid Picking-Delivery Strategy Genetic algorithm taboo searching algorithm Hybrid Genetic algorithm

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STUDY ON HYBRID HEURISTIC algorithm FOR MULTI-DEPOT VEHICLE ROUTING PROBLEM WITH HYBRID PICKING-DELIVERY STRATEGY

STUDY ON HYBRID HEURISTIC ALGORITHM FOR MULTI-DEPOT VEHICLE ...

引用

International Conference on Machine Learning and Cybernetics

作者： Wang, Xiao-Bo Sun, Jin-Ying Ren, Chun-Yu Heilongjiang Univ Sch Management Harbin 150080 Peoples R China Bldg Energy Engn Ctr China Architecture Design & Res Grp Beijing 100044 Peoples R China

ISBN: (纸本)9781424447053

With the rapid development of electronic commerce and logistics distribution, multi-depot vehicle routing problem with backhauls (MDVRPB) as influencing electronic commerce more step development, has been paid more attentions. According to the characteristics of model, hybrid heuristic algorithm is used to get the optimization solution. First of all, use hybrid coding so as to simplify the problem;construct the pertinence of initial solution to enhance the feasibility of solutions. Improved partially matched crossover operators can avoid destroying good gene parts during the course of crossover. According to the traditional genetic algorithm shortcomings of slowly convergent speed, the study adopts the strategy of protecting gene as whole, introduce adopts 2- exchange mutation operator. Secondly, stock elite adopting genetic algorithm with taboo searching algorithm to improve the convergent speed. This algorithm can offer the thought to settle the practical problem in scale. At the same time, it can be known that adopting hybrid picking-delivery strategy can save the distance of distribution route so as to improve economic benefit.

关键词： Vehicle routing problem with backhauls Stock elite Genetic algorithm taboo searching algorithm Hybrid heuristic algorithm

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Study on Hybrid Genetic algorithm for Hybrid Picking-Delivery Strategy Vehicle Routing Problem

Study on Hybrid Genetic Algorithm for Hybrid Picking-Deliver...

引用

2009中国控制与决策会议

作者： Ren Chunyu~1,Wang Xiaobo~1 1.School of Information Science and Technology,Heilongjiang University Harbin 150080

In order to satisfy with the individual and various demand of customer,establish vehicle scheduling with picking-delivery *** to the characteristics of model,hybrid genetic algorithm is used to get the optimization *** of all,use natural number coding so as to simplify the problem;use the individual amount control choice strategy so as to guarantee the diversity of *** ordinal crossover operators can avoid destroying good gene parts during the course of ordinal crossover so as that the algorithm can be convergent to the optimization as *** study adopts 2- exchange mutation operator to strengthen the partial searching ability of ***,stock elite adopting genetic algorithm take the hybrid genetic algorithm with taboo searching algorithm to improve the convergent speed and searching efficiency of *** algorithm has the characteristics of simple,clear and flexible and it can offer the thought to settle the practical problem in *** the same time,it can be known that adopting hybrid picking-delivery strategy can save the distance of distribution route so as to reduce company operating cost and improve economic benefit.

关键词： Vehicle Routing Problem Hybrid Picking-Delivery Strategy Genetic algorithm taboo searching algorithm Hybrid Genetic algorithm

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STUDY ON HYBRID HEURISTIC algorithm FOR MULTI-DEPOT VEHICLE ROUTING PROBLEM WITH HYBRID PICKING-DELIVERY STRATEGY

STUDY ON HYBRID HEURISTIC ALGORITHM FOR MULTI-DEPOT VEHICLE ...

引用

2009 International Conference on Machine Learning and Cybernetics(2009机器学习与控制论国际会议)

作者： CHUN-YU REN XIAO-BO WANG JIN-YING SUN School of management Heilongjiang University Harbin 150080 China Building Energy Engineering Center China Building Design Consultants China Architecture Design and

关键词： Vehicle routing problem with backhauls Stock elite Genetic algorithm taboo searching algorithm Hybrid heuristic algorithm

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