细菌觅食优化算法求解物流配送问题
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摘要
针对物流配送问题,在综合考虑时间、成本两个影响因素的前提下,提出一种针对离散多目标选址-路径问题(LRP)的改进细菌觅食优化算法。该算法通过构建相应的带软时间窗选址-路径问题模型,并根据Pareto支配关系对标准细菌觅食优化算法(BFOA)进行了改进,此外,在个体互不支配的时候,采用归一化方法进行择优处理,通过引入惩罚函数来约束车辆所负责的客户需求不超过其载重限制。设计的相应多目标细菌觅食优化算法(MOBFO)对物流配送问题进行了求解,并通过使用CVRP库中的算例,对算法的有效性和优劣性也进行了验证,对于LRP模型问题提供了一定的参考。实验结果表明,设计的多目标细菌觅食优化算法在求解物流配送问题上具有一定的优越性,同时对于多个目标的优化问题也具有一定的优势。
Aiming at the problem of fresh logistics distribution,on the premise of synthetically considering both time and cost,we propose an improved bacterial foraging optimization algorithm for location routing problem( LRP). This algorithm improves the standard bacterial foraging optimization algorithm( BFOA) by establishing the corresponding model with soft time window addressing-path problem on the basis of Pareto dominant relationship. In addition,when the individuals don't dominate each other,the normalized method is adopted to select the best,and the penalty function is introduced to restrict the customer demand of vehicle to not exceed its load limit. The corresponding multi-objective bacterial foraging optimization algorithm( MOBFOA) is designed to solve the problem of logistics distribution,and its effectiveness and advantages and disadvantages are also validated by using the examples of the CVRP library,which provides a certain reference for the LRP model problem. The experiment shows that the proposed algorithm had certain priority in solving logistics distribution problems and also certain advantages in the optimization of multiple objectives.
Aiming at the problem of fresh logistics distribution,on the premise of synthetically considering both time and cost,we propose an improved bacterial foraging optimization algorithm for location routing problem( LRP). This algorithm improves the standard bacterial foraging optimization algorithm( BFOA) by establishing the corresponding model with soft time window addressing-path problem on the basis of Pareto dominant relationship. In addition,when the individuals don't dominate each other,the normalized method is adopted to select the best,and the penalty function is introduced to restrict the customer demand of vehicle to not exceed its load limit. The corresponding multi-objective bacterial foraging optimization algorithm( MOBFOA) is designed to solve the problem of logistics distribution,and its effectiveness and advantages and disadvantages are also validated by using the examples of the CVRP library,which provides a certain reference for the LRP model problem. The experiment shows that the proposed algorithm had certain priority in solving logistics distribution problems and also certain advantages in the optimization of multiple objectives.
引文
[1]范立南,董冬艳,李佳洋,等.基于生鲜农产品的冷链物流配送路径优化[J].沈阳大学学报:自然科学版,2017,29(2):125-131.
[2]王晶,岳慧丽.基于时间窗约束的生鲜电商LRP问题研究[J].物流技术,2016,35(1):67-70.
[3] AMORIM P,ALMADA-LOBO B. The impact of food perishability issues in the vehicle routing problem[J]. Computers&Industrial Engineering,2014,67:223-233.
[4] ZANGENEH M,NIELSEN P,AKRAM A,et al. Agricultural service center location problem:concept and a M CDM solution approach[C]//IFIP international conference on advances in production management systems. Berlin:Springer,2014:611-617.
[5] KHALILI-DAMGHANI K,ABTAHI A R,GHASEMI A. A new bi-objective location-routing problem for distribution of perishable products:evolutionary computation approach[J].Journal of M athematical M odelling and Algorithms in Operations Research,2015,14(3):287-312.
[6]邵举平,曹倩,沈敏燕,等.生鲜农产品配送中带时窗的VRP模型与算法[J].工业工程与管理,2015,20(1):122-127.
[7]汤齐,张亚丽.基于时间约束的生鲜产品配送路径优化[J].铁道运输与经济,2016,38(6):40-43.
[8]何有世,马腾飞. B2C环境下生鲜农产品物流配送路径优化研究[J].商业经济研究,2017(5):93-95.
[9] CORNE D W,JERRAM N R,KNOWLES J D,et al. PESAII:region-based selection in evolutionary multiobjective optimization[C]//Proceedings of the 3rd annual conference on genetic and evolutionary computation. San Francisco,California:M organ Kaufmann Publishers Inc.,2001:283-290.
[10] DEB K,THIELE L,LAUMANNS M,et al. Scalable multiobjective optimization test problems[C]//Proceedings of the2002 congress on evolutionary computation. Honolulu,HI,USA:IEEE,2002:825-830.
[11] PASSINO K M. Biomimicry of bacterial foraging for distributed optimization and control[J]. IEEE Control Systems,2002,22(3):52-67.
[12]何家强.低碳化多源选址—路径—库存集成问题模型及算法研究[D].沈阳:东北大学,2012.
[13]公茂果,焦李成,杨咚咚,等.进化多目标优化算法研究[J].软件学报,2009,20(2):271-289.
[14]葛显龙,辜羽洁,谭柏川.基于第三方带软时间窗约束的车辆路径问题研究[J].计算机应用研究,2015,32(3):689-693.
[15]李珺,党建武.细菌觅食算法求解高维优化问题[J].计算机应用研究,2016,33(4):1024-1027.
[16]吕飞.考虑时间因素的选址-库存-路径问题集成优化模型与算法研究[D].武汉:华中师范大学,2011.
[2]王晶,岳慧丽.基于时间窗约束的生鲜电商LRP问题研究[J].物流技术,2016,35(1):67-70.
[3] AMORIM P,ALMADA-LOBO B. The impact of food perishability issues in the vehicle routing problem[J]. Computers&Industrial Engineering,2014,67:223-233.
[4] ZANGENEH M,NIELSEN P,AKRAM A,et al. Agricultural service center location problem:concept and a M CDM solution approach[C]//IFIP international conference on advances in production management systems. Berlin:Springer,2014:611-617.
[5] KHALILI-DAMGHANI K,ABTAHI A R,GHASEMI A. A new bi-objective location-routing problem for distribution of perishable products:evolutionary computation approach[J].Journal of M athematical M odelling and Algorithms in Operations Research,2015,14(3):287-312.
[6]邵举平,曹倩,沈敏燕,等.生鲜农产品配送中带时窗的VRP模型与算法[J].工业工程与管理,2015,20(1):122-127.
[7]汤齐,张亚丽.基于时间约束的生鲜产品配送路径优化[J].铁道运输与经济,2016,38(6):40-43.
[8]何有世,马腾飞. B2C环境下生鲜农产品物流配送路径优化研究[J].商业经济研究,2017(5):93-95.
[9] CORNE D W,JERRAM N R,KNOWLES J D,et al. PESAII:region-based selection in evolutionary multiobjective optimization[C]//Proceedings of the 3rd annual conference on genetic and evolutionary computation. San Francisco,California:M organ Kaufmann Publishers Inc.,2001:283-290.
[10] DEB K,THIELE L,LAUMANNS M,et al. Scalable multiobjective optimization test problems[C]//Proceedings of the2002 congress on evolutionary computation. Honolulu,HI,USA:IEEE,2002:825-830.
[11] PASSINO K M. Biomimicry of bacterial foraging for distributed optimization and control[J]. IEEE Control Systems,2002,22(3):52-67.
[12]何家强.低碳化多源选址—路径—库存集成问题模型及算法研究[D].沈阳:东北大学,2012.
[13]公茂果,焦李成,杨咚咚,等.进化多目标优化算法研究[J].软件学报,2009,20(2):271-289.
[14]葛显龙,辜羽洁,谭柏川.基于第三方带软时间窗约束的车辆路径问题研究[J].计算机应用研究,2015,32(3):689-693.
[15]李珺,党建武.细菌觅食算法求解高维优化问题[J].计算机应用研究,2016,33(4):1024-1027.
[16]吕飞.考虑时间因素的选址-库存-路径问题集成优化模型与算法研究[D].武汉:华中师范大学,2011.