基于混合算法的不确定环境下逆向物流网络设计研究

针对不确定环境下的逆向物流网络容易产生较高成本的问题,结合当前已有的物流设施节点,提出充分考虑固定投资、物流成本、库存成本和回收量不确定的设施选址规划模型,利用遗传算法和贪婪算法相结合的混合算法对设施选址、回收区域划分和回收间隔期进行求解。以某汽车零部件企业为实际案例,验证了模型和混合算法的可行性和正确性。     

需求和供应不确定下的选址研究

在需求不确定的同时,考虑了由于意外事件导致设施失灵而造成的供应不确定性,提出了这两个不确定因素下的设施选址模型.已知各个设施的失灵风险概率,通过情景规划描述需求不确定性,在保证供应系统的稳定性和鲁棒性不低于既定值的情况下,使得运输费用和设施失灵不能提供服务时的风险费用之和最小,提出了拉格朗日松弛算法,并通过大量算例验证...     

基于服务质量水平的随机逐渐覆盖模型与算法

覆盖问题在设施选址中占有重要的地位,有很高的研究价值和应用前景.在传统理论模型的基础上,从用户满意和服务质量水平的视角探讨逐渐覆盖问题.通过对覆盖函数的描述,对现有选址模型进行了改进,使得模型在实践中更具实用性.考虑到满足不同客户的需求标准和服务的公平性,建立了一个基于服务质量水平的随机逐渐覆盖选址模型,并给出了求解该模型的拉格朗日启发式算法.试验数据验证了该模型和算法在设施选址决策中的有效性.     

考虑市场扩张和吞并的新设施竞争选址模型

连锁型企业新设施的选址在市场扩张中占有至关重要的地位.提出了连锁型企业新设施进入产生两个结果:带来市场需求的扩张和对企业内部已存设施的市场侵蚀,建立了使连锁企业市场份额最大和企业内已存设施市场吞并最小的新设施选址的双目标模型,并给出了求解模型的遗传算法和具体的案例.结果表明该模型和算法可以用于连锁型企业新设施选址决策中,并能够有效的得到问题的近似解.     

基于工作负荷均衡的车辆拯救设施选址

交通事故车辆的拯救设施选址是车辆拯救服务的重要问题,选址不当易造成车辆拯救行业服务效率低下、市场行业的不规范、利益不均等一系列问题。针对这类问题,分析了俱乐部和政府引导两种服务模式下的拯救设施选址特点,并提出了针对车辆拯救的工作负荷概念。在不确定性救援路径行程时间条件下,建立以负荷均衡为目标的车辆拯救设施选址模型,以提高设施站点的运营效率和实现车辆拯救企业间的利益平衡。采用三种染色体形式的混合编码和随机模拟方法,设计基于遗传优化的求解算法。最后,通过仿真实例验证了算法的有效性。     

不确定环境下应急设施选址问题两阶段鲁棒优化模型

对于应急物流管理而言,应急物资集散中心选址是一个重要的决策要素。针对应急突发事件的不确定性特征,本文提出了一个应急设施选址问题两阶段鲁棒优化模型,以实现“预选址-重选址”两者的协同优化。第一阶段在需求和成本变动、设施损毁存在不确定因素的情况下,综合考虑选址策略在灾前规划、灾后反应、设施重建阶段的不同需求,建立了一种基于p-center的鲁棒“预选址”模型;第二阶段针对灾后新信息的获得,建立了一种基于反应式修复和调整策略的新建设施“重选址”模型。算例分析表明,本文模型对于应急设施选址问题比传统p-center模型更为合理有效     

一类多产品设施选址问题研究

对一类多产品设施选址问题进行了描述,通过分析得出该类设施选址问题可转化为分配问题,从而可通过匈牙利法对该设施选址问题进行简便地求解.最后给出了该类多产品设施选址问题的求解范例.     

竞争环境中的截流选址与设计问题

研究了在竞争环境下同时优化选址和设计决策的截流选址问题。产生于网络路径上的顾客流按一定概率分布来选择各个设施,概率分布由设施服务台数量与偏移原路径距离共同决定。在已有竞争设施存在的情况下,通过选址和设计服务台数量的决策使净收益最大。采用一种带权重的贪婪算法来求解该问题,经过大量计算实验表明该方法求解质量和求解速度都比较理想。     

综合模糊TOPSIS决策的应急物资储备库多级覆盖选址模型

研究应急物资储备库选址理论和方法在应对当前频发的重大突发事件具有重要的现实意义和理论价值。针对现有设施选址理论存在的局限性,提出综合模糊TOPSIS决策的应急物资储备库多级覆盖选址模型。在分析应急物资储备库选址影响因素的基础上,构建应急物资储备库选址评价指标体系,运用模糊TOPSIS方法对候选应急物资储备库进行初选;基于"备用覆盖"和"部分覆盖"思想,建立应急物资储备库多级覆盖选址模型,运用遗传算法对模型求解,确定最终选址方案;以一个算例对算法进行验证,分析了算法的有效性。     

基于分级选址模型的学校选址问题

考虑到我国中小学选址问题的特性,本文引入分段效用函数,综合考虑距离、服务质量等多种选址因素,提出基于效用函数的分级的带容量限制的中位模型。模型约束条件包括需求的全覆盖、设施的最小容量约束、需求点就近分配给设施点、需求点单一分配给设施点及开放与关闭设施数目限制等。本文使用拉格朗日松弛算法,以武汉市经济技术开发区为例,就目前学校选址及分配的合理性问题、学校最小容量的合理设置问题和需求波动后的重新选址及分配问题进行了分析。     

Facility location under uncertainty: a review

Plants, distribution centers, and other facilities generally function for years or decades, during which time the environment in which they operate may change substantially. Costs, demands, travel times, and other inputs to classical facility location models may be highly uncertain. This has made the development of models for facility location under uncertainty a high priority for researchers in both the logistics and stochastic/robust optimization communities. Indeed, a large number of the approaches that have been proposed for optimization under uncertainty have been applied to facility location problems. This paper reviews the literature on stochastic and robust facility location models. Our intent is to illustrate both the rich variety of approaches for optimization under uncertainty that have appeared in the literature and their application to facility location problems. In a few instances for which examples in facility location are not available, we provide examples from the more general logistics literature.     

Location and layout planning

This paper gives a review on quantitative methods for microeconomic location planning which can be subdivided into facility location and layout planning. Depending on different objectives and restrictions, there is a large variety of problems, especially in the field of facility location planning. Basic models arising in discrete and continuous facility location planning (e.g., warehouse location, center, location routing, competitive location problems), as well as corresponding solution methods, are presented. Generalized models and recent developments in these fields are outlined. Within layout planning, the quadratic assignment problem and graph-theoretic concepts are considered.     

A modeling framework for facility location of medical services for large-scale emergencies

Research on facility location is abundant. However, this research does not typically address the particular conditions that arise when locating facilities to service large-scale emergencies, such as earthquakes, terrorist attacks, etc. In this work we first survey general facility location problems and identify models used to address common emergency situations, such as house fires and regular health care needs. We then analyze the characteristics of large-scale emergencies and propose a general facility location model that is suited for large-scale emergencies. This general facility location model can be cast as a covering model, a P-median model or a P-center model, each suited for different needs in a large-scale emergency. Illustrative examples are given to show how the proposed model can be used to optimize the locations of facilities for medical supplies to address large-scale emergencies in the Los Angeles area. Furthermore, comparison of the solutions obtained by respectively using the proposed model and the traditional model is given to show the benefits of the proposed model in reducing loss of life and economic losses.     

Supply chain network design with unreliable suppliers: a Lagrangian relaxation-based approach

This paper deals with the integrated facility location and supplier selection decisions for the design of supply chain network with reliable and unreliable suppliers. Two problems are addressed: (1) facility location/supplier selection; and (2) facility location/supplier reliability. We first consider the facility location and supplier selections problem where all the suppliers are reliable. The decisions concern the selection of suppliers, the location of distribution centres (DCs), the allocation of suppliers to DCs and the allocation of retailers to DCs. The objective is to minimise fixed DCs location costs, inventory and safety stock costs at the DCs and ordering costs and transportation costs across the network. The introduction of inventory costs and safety stock costs leads to a non-linear NP-hard optimisation problem. To solve this problem, a Lagrangian relaxation-based approach is developed. For the second problem, a two-period decision model is proposed in which selected suppliers are reliable in the first period and can fail in the second period. The corresponding facility location/supplier reliability problem is formulated as a non-linear stochastic programming problem. A Monte Carlo optimisation approach combining the sample average approximation scheme and the Lagrangian relaxation-based approach is proposed. Computational results are presented to evaluate the efficiency of the proposed approaches.     

Optimal axis orientation for rectilinear minisum and minimax location

This paper considers the rectilinear minisum and minimax location problems from a different point of view in that the orientation of the axes, which define the distances, is now also to be optimized. This corresponds to the situation where the grid of roads or aisles which connects the demand points to the facility, can be designed at the same time as the location of the facility is chosen. Optimization methods are presented for both problems.     

The facility location problem from the perspective of triple bottom line accounting of sustainability

Design of facilities network, allocation of customers to be served from the facilities and their operations have strong economic, environmental and social impacts. Although the decisions in the facility location problem may have varying effects on these impacts, simultaneous consideration of these effects in the early stages of decision-making for facility location selection and network plan has attracted limited attention in the facility location decision literature. Specifically, the social dimension and mathematical modelling are rarely used. In this paper, we present a decision support framework for the facility location problem that incorporates the triple bottom line accounting of sustainability. The framework is a valuable integration of mathematical modelling embedding the criteria with proper measurement indicators in a multi-objective model, perspectives of the related stakeholders, any thresholds and assumption, model analysis, and the decision-maker strategy to find the best-fit alternative. We demonstrate our methodological approach to establish a supply network for digital products in Turkey using real data. The results indicate that the method can balance the economic, environmental and social pillars, based on limitations of the three pillars and strategic perspective of the decision-maker. The decision-maker can interpret the interactions among the three pillars of sustainability and can make his decision by analysing the balance between them.     

A multi-objective mixed-integer programming model for a multi-floor facility layout

We consider a multi-floor facility layout problem in which the overall length and width of the facility, the size and location of each department, the number and the location of elevators and the number of floors in the facility are all modelled as decision variables. We adapt a linear approximation scheme to represent the area of each department. We consider two objective functions in our model, namely minimising material handling and facility building costs, and propose a lexicographic ordering technique to handle multiple objectives. The numerical experiments show that the slack used in the lexicographic ordering approach has a significant impact on the optimal solution. The experiments also show that the material handling cost can be significantly reduced in a multi-floor facility compared with a single-floor facility.     

Generalized hull properties for location problems

This paper considers a general form of the single facility minisum location model, also known as the Fermat-Weber problem, in which the cost components are increasing differentiable functions of a norm. In particular, attention is restricted to a broad class of norms referred to as round norms, a formal definition of which is included. It is shown that all locally optimal locations of the new facility in the two-dimensional problem (N-dimensional for the Euclidean norm) must be within the convex hull of the destinations. The results are extended to a general form of the multifacility minisum location problem.     

A knowledge-based decision support system for locating a manufacturing facility

This paper examines the design and implementation of a knowledge-based decision support system (KBDSS) in the facility location domain. The KBDSS for locating a manufacturing facility is intended to support facilities planners in improving the quality of strategic decision-making in facility location. A survey of past location studies was conducted to identify the major considerations of location analysts and to develop a hierarchy of factors for locating a manufacturing facility in the USA. Location evaluation is accomplished via a location model that is formulated as a linear additive multiattribute utility model. The microcomputer-based DSS developed integrates an object-oriented expert system with other modeling tools, such as a database management system and a C-based interactive graphical user interface. The system incorporates subjective, judgemental evaluations from management with objective, factual location data to recommend the best location for a new manufacturing facility. The system also makes transparent the justification for its recommendations by providing appropriate textual and graphical explanation facilities.