多粒度语言信息的交互式多属性群决策方法及应用

针对目前多阶段交互式决策的研究多是基于点值的缺陷,以及大多数研究忽视了从多个属性对方案进行评价等不足,本文探讨了一种基于多粒度语言信息的交互式多属性群决策方法。首先基于不确定语言变量提出了多粒度语言信息的转换函数,并在给出若干假设的前提下描述了交互式多属性群决策的过程,然后提出了交互影响因子来度量决策者的“话语权”,通过稳定性指标探讨交互终止条件;接着在不确定语言变量的加权算术平均(ULWA)算子和诱导多阶段交互加权算子(I-UOWA和I-UOWGA)的基础上对偏好信息进行集结,再提出优势可能度法对方案排序。最后给出了一个物流供应商选择的案例研究。     

电商绿色物流生态体系目标优化实证研究

当前电商日益走进我国经济社会生活的方方面面,物流业与电商相伴高速成长,人们生态环保意识的加强推动了电商绿色物流体系的发展。本文基于生态系统理论,探究电商与物流有机融合,探讨了电商物流绿色体系构建的影响因素,并进一步探讨了电商物流绿色生态体系的边界。基于此,本文还构建了电商物流生态体系多因素目标优化模型与层次分析法相结合的评价方法,在各指标之间的权重方面,以专家问询结合层次分析法量化了各指标的权重,得到基于调研企业的最终评价得分,用以评估企业在电商绿色物流生态体系各方面的具体表现。     

Scheduling the part supply of mixed-model assembly lines in line-integrated supermarkets

Line-integrated supermarkets constitute a novel in-house parts logistics concept for feeding mixed-model assembly lines. In this context, supermarkets are decentralized logistics areas located directly in each station. Here, parts are withdrawn from their containers by a dedicated logistics worker and sorted just-in-sequence (JIS) into a JIS-bin. From this bin, assembly workers fetch the parts required by the current workpiece and mount them during the respective production cycle. This paper treats the scheduling of the part supply processes within line-integrated supermarkets. The scheduling problem for refilling the JIS-bins is formalized and a complexity analysis is provided. Furthermore, a heuristic decomposition approach is presented and important managerial aspects are investigated.     

基于前景理论的众包物流配送方行为决策演化博弈分析——基于发货方视角

考虑个体有限理性特征,基于前景理论构建众包物流参与者感知收益博弈矩阵。从发货方视角,推理出众包物流配送方发挥较高努力水平的条件。通过引入保价制度,建立保价条件下配送方的行为决策模型,并运用数值仿真技术验证模型的有效性。结果发现:(1)配送方的努力成本、不努力的收入、处罚力度等指标直接影响其努力水平;(2)配送方努力工作的成本前景值要小于受到处罚与不努力收入前景值之和,同时要小于努力工作时所得的收益;(3)保价金额变动在一定条件下会影响配送方的努力水平,但是并不能达到完全控制的目的,甚至造成负面影响。因此在保价基础上,发货方可以通过增加监测力度或者加大处罚力度,有效保证配送方的努力水平。     

Selective capacitated location-routing problem with incentive-dependent returns in designing used products collection network

This paper addresses a generalization of the capacitated location-routing problem (CLRP) arising in the design of a collection network for a company engaged in collecting used products from customer zones. The company offers customers a financial incentive per unit of used products. This incentive determines the quantity of used products which are returned by customers. Moreover, it is not necessary for the company to visit all customer zones or to collect all returns in each visited customer zone. The objective is to simultaneously find the location of collection centers, the routes of vehicles, the value of incentive offered and the amount of used products collected from customer zones, so as to maximize the company's overall profit. We develop two mixed integer linear programming formulations of the problem and a heuristic algorithm based on iterated local search. Extensive computational experiments on this problem demonstrate the effectiveness of the proposed algorithm.     

我国农村地区开展BtoC电子商务物流配送的新模式——基于区域客运班车系统的配送解决方案

针对我国农村地区开展区域BtoC电子商务物流配送成本高、时间长、配送体系不完善的问题,提出基于区域客运班车系统的配送解决方案,设计了整体框架,作业流程,并对解决配送路线选择这一关键问题提出相应的求解算法.     

物流中心选址的多目标优化模型

针对一个经纬型网络中的最优选址问题,借鉴选址问题的已有理论和方法,建立了一个新的数学模型.研究了该模型的实际可行算法,结果表明该算法所求解是最优的,为运输、供销、物流系统的实际部门提供了有效的方法.     

区际救援物资中转调度的动态决策模型与算法

考虑灾害救援中灾区对应急物资的持续消耗,研究了区际多品种救援物资的动态中转调度问题.综合考虑各阶段调度费用、运输费用和库存费用总和最小化的救援物资中转调度安排和库存规划,建立了一个区际救援物资中转调度动态决策模型,并设计了一种矩阵编码的协进化遗传算法.最后通过一个算例验证了模型和算法的有效性.     

A robust optimization approach to closed-loop supply chain network design under uncertainty

The concern about significant changes in the business environment (such as customer demands and transportation costs) has spurred an interest in designing scalable and robust supply chains. This paper proposes a robust optimization model for handling the inherent uncertainty of input data in a closed-loop supply chain network design problem. First, a deterministic mixed-integer linear programming model is developed for designing a closed-loop supply chain network. Then, the robust counterpart of the proposed mixed-integer linear programming model is presented by using the recent extensions in robust optimization theory. Finally, to assess the robustness of the solutions obtained by the novel robust optimization model, they are compared to those generated by the deterministic mixed-integer linear programming model in a number of realizations under different test problems.     

The two-echelon capacitated electric vehicle routing problem with battery swapping stations: Formulation and efficient methodology

In this paper, we present a two-echelon capacitated electric vehicle routing problem with battery swapping stations (2E-EVRP-BSS), which aims to determine the delivery strategy under battery driving range limitations for city logistics. The electric vehicles operating in the different echelons have different load capacities, battery driving ranges, power consumption rates, and battery swapping costs. We propose an integer programming formulation and a hybrid algorithm that combines a column generation and an adaptive large neighborhood search (CG-ALNS) to solve the problem. We conducted extensive computational experiments, demonstrate the applicability of the proposed model, and show the efficiency of the CG-ALNS algorithm. In addition, we explore the interplay between battery driving range and the effectiveness of vehicle emission reduction through sensitivity analysis.