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
Estimation of stochastic demand in physical distribution in general and efficient transport routs management in particular is emerging as a crucial factor in urban planning domain. It is particularly important in some...Estimation of stochastic demand in physical distribution in general and efficient transport routs management in particular is emerging as a crucial factor in urban planning domain. It is particularly important in some municipalities such as Tehran where a sound demand management calls for a realistic analysis of the routing system. The methodology involved critically investigating a fuzzy least-squares linear regression approach (FLLRs) to estimate the stochastic demands in the vehicle routing problem (VRP) bearing in mind the customer's preferences order. A FLLR method is proposed in solving the VRP with stochastic demands: approximate-distance fuzzy least-squares (ADFL) estimator ADFL estimator is applied to original data taken from a case study. The SSR values of the ADFL estimator and real demand are obtained and then compared to SSR values of the nominal demand and real demand. Empirical results showed that the proposed method can be viable in solving problems under circumstances of having vague and imprecise performance ratings. The results further proved that application of the ADFL was realistic and efficient estimator to face the sto- chastic demand challenges in vehicle routing system management and solve relevant problems.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Estimation of stochastic demand in physical distribution in general and efficient transport routs management in particular is emerging as a crucial factor in urban planning domain. It is particularly important in some municipalities such as Tehran where a sound demand management calls for a realistic analysis of the routing system. The methodology involved critically investigating a fuzzy least-squares linear regression approach (FLLRs) to estimate the stochastic demands in the vehicle routing problem (VRP) bearing in mind the customer's preferences order. A FLLR method is proposed in solving the VRP with stochastic demands: approximate-distance fuzzy least-squares (ADFL) estimator ADFL estimator is applied to original data taken from a case study. The SSR values of the ADFL estimator and real demand are obtained and then compared to SSR values of the nominal demand and real demand. Empirical results showed that the proposed method can be viable in solving problems under circumstances of having vague and imprecise performance ratings. The results further proved that application of the ADFL was realistic and efficient estimator to face the sto- chastic demand challenges in vehicle routing system management and solve relevant problems.
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%.
