Due to the problem complexity, simultaneous solution methods are limited. A hybrid algorithm is emphatically proposed for LRP. First, the customers are classified by clustering analysis with preference-fitting rules. ...Due to the problem complexity, simultaneous solution methods are limited. A hybrid algorithm is emphatically proposed for LRP. First, the customers are classified by clustering analysis with preference-fitting rules. Second, a chaos search (CS) algorithm for the optimal routes of LRP scheduling is presented in this paper. For the ergodicity and randomness of chaotic sequence, this CS architecture makes it possible to search the solution space easily, thus producing optimal solutions without local optimization. A case study using computer simulation showed that the CS system is simple and effective, which achieves significant improvement compared to a recent LRP with nonlinear constrained optimization solution. Lastly the pratical anlysis is presented relationship with regional logistics and its development in Fujian province.展开更多
In this paper,a novel location inventory routing(LIR)model is proposed to solve cold chain logistics network problem under uncertain demand environment. The goal of the developed model is to optimize costs of location...In this paper,a novel location inventory routing(LIR)model is proposed to solve cold chain logistics network problem under uncertain demand environment. The goal of the developed model is to optimize costs of location,inventory and transportation.Due to the complex of LIR problem( LIRP), a multi-objective genetic algorithm(GA), non-dominated sorting in genetic algorithm Ⅱ( NSGA-Ⅱ) has been introduced. Its performance is tested over a real case for the proposed problems. Results indicate that NSGA-Ⅱ provides a competitive performance than GA,which demonstrates that the proposed model and multi-objective GA are considerably efficient to solve the problem.展开更多
The location of the distribution facilities and the routing of the vehicles from these facilities are interdependent in many distribution systems. Such a concept recognizes the interdependence;attempts to integrate th...The location of the distribution facilities and the routing of the vehicles from these facilities are interdependent in many distribution systems. Such a concept recognizes the interdependence;attempts to integrate these two decisions have been limited. Multi-objective location-routing problem (MLRP) is combined with the facility location and the vehicle routing decision and satisfied the different objectives. Due to the problem complexity, simultaneous solution methods are limited, which are given in different objectives with conflicts in functions satisfied. Two kinds of optimal mathematical models are proposed for the solution of MLRP. Three methods have been emphatically developed for MLRP. MGA architecture makes it possible to search the solution space efficiently, which provides a path for searching the solution with two-objective LRP. At last the practical proof is given by random analysis for regional distribution with nine cities.展开更多
目的针对当前物流背景下普遍出现的送货公司外包、退换货频繁等问题,结合现有的碳排放政策,提出低碳背景下开放式同时送取货选址−路径模型(Low-Carbon Open Location-routing Problem with Simultaneous Pickup and Delivery Problem,LO...目的针对当前物流背景下普遍出现的送货公司外包、退换货频繁等问题,结合现有的碳排放政策,提出低碳背景下开放式同时送取货选址−路径模型(Low-Carbon Open Location-routing Problem with Simultaneous Pickup and Delivery Problem,LOLRPSPD),并通过改进野马算法进行求解。方法首先设计一种新的解码方式,使得原离散问题可以采用连续算法求解。之后,运用哈尔顿序列生成初始解,改进非线性进化概率因子,使用模拟二进制交叉,增加变异操作,以及精英保留、设置连续失败重新初始化等步骤,改进野马算法。最后,通过6组不同大小的算例将改进野马算法与原始野马算法、模拟退火算法、粒子群算法、遗传算法进行对比。结果针对中大型算例,改进野马算法远超原始野马算法。针对小型算例,在确保准确率的同时,改进野马算法对比各经典算法也在速度上具有优势。结论提出的LOLRPSD模型具备合理性,改进的野马算法针对选址路径问题具有较好的搜索能力。展开更多
为了解决危险废物回收、加工和处理中心选址问题,确定加工技术类别、安排危险废物和废物残余车辆运输路径,将回收环节纳入危险废物物流系统,考虑废物类型与加工技术的多样性、中心运营费用、废物与加工技术的相容性以及中心能力富余量约...为了解决危险废物回收、加工和处理中心选址问题,确定加工技术类别、安排危险废物和废物残余车辆运输路径,将回收环节纳入危险废物物流系统,考虑废物类型与加工技术的多样性、中心运营费用、废物与加工技术的相容性以及中心能力富余量约束,以费用和风险最小化为优化目标,建立了危险废物物流系统的改进多目标0-1混合整数线性规划模型.采用TOPSIS(technique for order preference by similarity to an ideal solution)方法求解模型.结果表明,与现有模型相比,本文模型的多目标优化方案以增加0.70%的费用为代价,将风险降低7.69%.展开更多
文摘Due to the problem complexity, simultaneous solution methods are limited. A hybrid algorithm is emphatically proposed for LRP. First, the customers are classified by clustering analysis with preference-fitting rules. Second, a chaos search (CS) algorithm for the optimal routes of LRP scheduling is presented in this paper. For the ergodicity and randomness of chaotic sequence, this CS architecture makes it possible to search the solution space easily, thus producing optimal solutions without local optimization. A case study using computer simulation showed that the CS system is simple and effective, which achieves significant improvement compared to a recent LRP with nonlinear constrained optimization solution. Lastly the pratical anlysis is presented relationship with regional logistics and its development in Fujian province.
基金Natural Science Foundation of Shanghai,China(No.15ZR1401600)the Fundamental Research Funds for the Central Universities,China(No.CUSF-DH-D-2015096)
文摘In this paper,a novel location inventory routing(LIR)model is proposed to solve cold chain logistics network problem under uncertain demand environment. The goal of the developed model is to optimize costs of location,inventory and transportation.Due to the complex of LIR problem( LIRP), a multi-objective genetic algorithm(GA), non-dominated sorting in genetic algorithm Ⅱ( NSGA-Ⅱ) has been introduced. Its performance is tested over a real case for the proposed problems. Results indicate that NSGA-Ⅱ provides a competitive performance than GA,which demonstrates that the proposed model and multi-objective GA are considerably efficient to solve the problem.
文摘The location of the distribution facilities and the routing of the vehicles from these facilities are interdependent in many distribution systems. Such a concept recognizes the interdependence;attempts to integrate these two decisions have been limited. Multi-objective location-routing problem (MLRP) is combined with the facility location and the vehicle routing decision and satisfied the different objectives. Due to the problem complexity, simultaneous solution methods are limited, which are given in different objectives with conflicts in functions satisfied. Two kinds of optimal mathematical models are proposed for the solution of MLRP. Three methods have been emphatically developed for MLRP. MGA architecture makes it possible to search the solution space efficiently, which provides a path for searching the solution with two-objective LRP. At last the practical proof is given by random analysis for regional distribution with nine cities.
文摘目的针对当前物流背景下普遍出现的送货公司外包、退换货频繁等问题,结合现有的碳排放政策,提出低碳背景下开放式同时送取货选址−路径模型(Low-Carbon Open Location-routing Problem with Simultaneous Pickup and Delivery Problem,LOLRPSPD),并通过改进野马算法进行求解。方法首先设计一种新的解码方式,使得原离散问题可以采用连续算法求解。之后,运用哈尔顿序列生成初始解,改进非线性进化概率因子,使用模拟二进制交叉,增加变异操作,以及精英保留、设置连续失败重新初始化等步骤,改进野马算法。最后,通过6组不同大小的算例将改进野马算法与原始野马算法、模拟退火算法、粒子群算法、遗传算法进行对比。结果针对中大型算例,改进野马算法远超原始野马算法。针对小型算例,在确保准确率的同时,改进野马算法对比各经典算法也在速度上具有优势。结论提出的LOLRPSD模型具备合理性,改进的野马算法针对选址路径问题具有较好的搜索能力。
文摘为了解决危险废物回收、加工和处理中心选址问题,确定加工技术类别、安排危险废物和废物残余车辆运输路径,将回收环节纳入危险废物物流系统,考虑废物类型与加工技术的多样性、中心运营费用、废物与加工技术的相容性以及中心能力富余量约束,以费用和风险最小化为优化目标,建立了危险废物物流系统的改进多目标0-1混合整数线性规划模型.采用TOPSIS(technique for order preference by similarity to an ideal solution)方法求解模型.结果表明,与现有模型相比,本文模型的多目标优化方案以增加0.70%的费用为代价,将风险降低7.69%.
