时间满意逐渐覆盖电动汽车充电站选址及算法

作为电动汽车配套的基础设施,电动汽车充电站的选址对电动汽车的推广有着十分重要的意义.针对电动汽车充电站选址问题,别入逐渐覆盖思想和时间满意度函数,从需求点效用最大化的角度出发,提出了基于时间满意逐渐覆盖电动汽车充电站选址模型,并运用蝙蝠算法通过MATLAB实现.实例的求解比较验证了该模型及算法在电动汽车充电站选址决策中的有效性.     

应急资源需求周期性变化的选址与资源配置模型

本文提出了应急资源需求周期性变化的选址与资源配置模型.在规划选址阶段,针对于需求周期性变化的情况,把选址与各个时间段的资源配置结合起来确定建造服务设施地点,使得选址能够兼顾到各个需求点,在所有需求点一定比例需求量均被满足的前提下,使一个周期内需求点被满足的总需求量最大化.根据模型特点设计算法,解决了两目标非线性整数规划求解困难的问题,最后通过算例说明了本模型和算法是有效的.     

基于加权绝对值距离Steiner最优树的选址问题

提出基于加权绝对值距离Steiner最优树思想的选址模型,给出了该模型的蚂蚁算法实现策略.在此基础上,分析了电子商务环境下企业配送中心选址问题,并用算例验证了该选址方案的可行性.     

线状需求下的长江航道危险品应急中心选址优化

本文分析了长江航道危险品船舶对应急中心救援服务的线状需求特征,基于点状需求的设施选址模型,构建了全覆盖下的最小成本选址模型,实现了线状需求特性与最小成本的最优结合。将点状需求的设施选址研究延伸到线状需求的设施选址研究领域。并且针对模型设计了确定性规划算法和遗传算法。最后以长江航道为具体算例,对比了确定性规划算法和遗传算法对模型进行求解的效率及精度。实例表明,本文建立的基于线状需求的应急中心选址模型是符合实际的,确定性规划算法相对于遗传算法可以在更短时间内求得较稳定的最优解;遗传算法运行时间相对较长,且结果稳定性较差。     

电动汽车充电站选址问题研究

研究了电动汽车作为通勤工具情况下的充电站选址问题.首先根据城市通勤道路长度、各条道路上的通勤人员拟使用电动汽车的数量,以及电动汽车的最大续航里程等信息,构建了包含两种边的赋权网络图,进一步将电动汽车充电站选址问题转化为赋权网络图的最大覆盖问题,并建立了以极大化满足用户需求为目标的充电站选址问题整数非线性规划模型,设计了求解模型的启发式算法.最后,通过一个具体算例对模型及算法进行了验证,结果显示,模型和算法是解决电动汽车充电站选址问题有效方法.     

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.     

电子商务背景下的城市物流共享仓库动态选址研究

针对电商顾客需求波动较大、分布较广、时效性较强等特点,首次将顾客需求的波动性及仓库资源的共享性等因素引入动态选址问题,并综合考虑运输成本、租赁共享仓库成本、关闭成本及风险成本等因素,以总成本最小为目标,构建了电子商务背景下的物流共享仓库动态选址模型.针对模型的NP难特性,提出了一种改进的遗传算法来求解该模型.最后,通过算例验证了模型的可行性及算法的有效性.     

多类型需求流的截流选址问题研究和算法实现

本文研究了网络上固定的O-D对上存在不同类型的需求流的选址问题。在基本截流模型的基础上提出了多类型需求流多目标截流选址问题的模型,将模型转化为多目标模糊规划问题,运用混合遗传算法求解模型,最后给出了算例,并与分支定界法相比,证明了混合遗传算法可以有效的求解此模型。     

种群规模自适应粒子群在配送中心连续型选址中的应用

本文依照更具有现实意义的“加工厂—配送中心—用户”的模式建立物流配送中心连续型选址模型,并针对较大规模的选址问题提出求解算法。该算法是将具有较强鲁棒性的自适应粒子算法和改进的ALA(Alert Location-Allocation)方法结合而得,该算法中种群规模自适应变化,对经典粒子移动方程进行改进,消除了学习因子,惯性因子随粒子适应值自适应变化,改进的ALA方法提高了算法计算效率。数值试验表明,本文所建模型具有一定的实践优越性,所提出的算法能有效避免陷入局部最优,寻优能力和鲁棒性均较强。     

一类应急服务设施选址问题的模型及算法

在分析城市应急服务设施选址问题基础上,建立了限定期条件下应急服务设施选址问题的数学模型,提出了一种基于遗传算法的应急服务设施选址模型的有效算法,并通过算例分析验证了该方法的有效性.     

Network production-location problems under price uncertainty

The scope of the network plant location problem is extended in three significant ways: (i) The ‘design’ of the facility, including consideration of input substitution and the level of output, is combined with the location decision; (ii) input and output prices are treated as random variables, and (iii) the risk preferences of the decision maker are considered explicitly in the decision making process. Node optimality properties are developed for several model variations. An elimination-by-bound solution algorithm is presented along with suggested upper and lower bounds and methods of simplification. Under certain conditions, the optimal input ratios and plant locations are shown to be invariant with some parametric changes. The potential for influencing the location decisions of firms, depending upon the characteristics of their risk preferences, production functions, and the demand functions for their input, through manipulation of the risk they face, is illustrated.     

Robust supply chain network design with multi-products for a company in the food sector

The paper aims to solve a problem faced by a company competing in the snacks market in Turkey. In line with the growth in this market, the company needs to make important decisions over the next few years about the timing and location of a new plant, its initial capacity, the timing and amount of additional capacity to be installed at the new and existing plants, the assignment of demand points to plants and the amount of raw materials to be shipped from suppliers to the plants in each period. The objective is to minimize the total cost of various components. The problem is formulated as a multi-period supply chain network design model with multi products. The resulting mixed-integer linear programming model is solved by the commercial solver CPLEX. This model enables us to carry out all analyses requested by the company in an efficient way. After this deterministic model is solved on the basis of a 9% annual increase in demand, it is extended to a minimax regret model to deal with uncertainty in demand quantities. The results suggest that opening the new plant in the city of İzmir is indeed a robust solution that is unaffected in different scenarios that are based on three distinct demand increase rates. Even though the location of the new plant remains unchanged with respect to scenarios, the optimal robust solution differs from the optimal solution of each scenario in terms of the capacity expansion decisions. After all obtained results had been communicated to the company managers and executives, the new plant construction was started in 2016 very close to the city that the mathematical model had determined. The new plant is expected to start operating in 2018.     

Dynamic dairy facility location and supply chain planning under traffic congestion and demand uncertainty: A case study of Tehran

In this paper, dynamic dairy facility location and supply chain planning are studied through minimizing the costs of facility location, traffic congestion and transportation of raw/processed milk and dairy products under demand uncertainty. The proposed model dynamically incorporates possible changes in transportation network, facility investment costs, monetary value of time and changes in production process. In addition, the time variation and the demand uncertainty for dairy products in each period of the planning horizon is taken into account to determine the optimal facility location and the optimal production volumes. Computational results are presented for the model on a number of test problems. Also, an empirical case study is conducted in order to investigate the dynamic effects of traffic congestion and demand uncertainty on facility location design and total system costs.     

A Plant and Warehouse Location Problem

A model is proposed for the simultaneous location of plants and warehouses among a given set of possible locations in order to satisfy a given demand at minimum cost. The demand of each customer may be satisfied directly from a plant or through a warehouse. The model also applies to the design of a distribution network with two levels of warehouses. A branch-and-bound algorithm, which generalizes previous work by Efroymson and Ray and others, is presented, computational experience is reported on.     

Valid inequalities and facets of the capacitated plant location problem

Recently, several successful applications of strong cutting plane methods to combinatorial optimization problems have renewed interest in cutting plane methods, and polyhedral characterizations, of integer programming problems. In this paper, we investigate the polyhedral structure of the capacitated plant location problem. Our purpose is to identify facets and valid inequalities for a wide range of capacitated fixed charge problems that contain this prototype problem as a substructure.The first part of the paper introduces a family of facets for a version of the capacitated plant location problem with a constant capacity for all plants. These facet inequalities depend on the capacity and thus differ fundamentally from the valid inequalities for the uncapacited version of the problem.We also introduce a second formulation for a model with indivisible customer demand and show that it is equivalent to a vertex packing problem on a derived graph. We identify facets and valid inequalities for this version of the problem by applying known results for the vertex packing polytope.This research was partially supported by Grant # ECS-8316224 from the National Science Foundation's Program in Systems Theory and Operations Research.     

Modelling lost demand in competitive facility location

In this paper, we propose a simple new approach to model lost demand (also referred to as elastic demand) in competitive facility location. A ‘dummy’ competing facility that attracts the lost demand is added to the list of competing facilities. All competitive facility location models, regardless of their complexity or assumptions, can be modified to include lost demand and be solved by the same algorithms designed for standard models once the dummy facility is added to the data as an additional competitor.     

Capacitated facility location/network design problems

We introduce a combined facility location/network design problem in which facilities have constraining capacities on the amount of demand they can serve. This model has a number of applications in regional planning, distribution, telecommunications, energy management, and other areas. Our model includes the classical capacitated facility location problem (CFLP) on a network as a special case. We present a mixed integer programming formulation of the problem, and several classes of valid inequalities are derived to strengthen its LP relaxation. Computational experience with problems with up to 40 nodes and 160 candidate links is reported, and a sensitivity analysis provides insight into the behavior of the model in response to changes in key problem parameters.     

大规模风电并网的双供应源电力供应链牛鞭效应分析

中国当前的电力供应链除具有部分垄断特征外,还由于大规模风电并网使得电力供给也出现随机性,它与随机需求一起影响了供应链信息的准确传递,在电力供应链产生了牛鞭效应,但对这类问题的研究极少。本文在分析中国电力供应链特点的基础上,构建了由煤炭供应企业、发电厂(火力发电和风力发电)和用户组成的多级电力供应链模型,揭示了牛鞭效应在单/双供应源两种供应链类型下的变化。研究结果表明,大规模风电并网形成的双供应源电力供应链牛鞭效应较大且波动剧烈,尤其当下游用户需求较平稳时,供应链会出现牛鞭效应与反牛鞭效应共存现象,而预测技术的选择、风电场合理规划等有助于抑制牛鞭效应,保证电力安全并减小资源浪费。     

A comparative study of modeling and solution approaches for the coordinated lot-size problem with dynamic demand

In the coordinated lot-size problem, a major setup cost is incurred when at least one member of a product family is produced and a minor setup cost for each different item produced. This research consolidates the various modeling and algorithmic approaches reported in the literature for the coordinated replenishment problem with deterministic dynamic demand. For the two most effective approaches, we conducted extensive computational experiments investigating the quality of the lower bound associated with the model’s linear programming relaxation and the computational efficiency of the algorithmic approaches when used to find heuristic and optimal solutions. Our findings indicate the superiority of the plant location type problem formulation over the traditional approach that views the problem as multiple single-item Wagner and Whitin problems that are coupled by major setup costs. Broader implications of the research suggest that other classes of deterministic dynamic demand lot-size problems may also be more effectively modeled and solved by adapting plant location type models and algorithms.     

Global plant capacity and product allocation with pricing decisions

Trade-offs in global manufacturing decisions involve markets, resource costs, trade-barriers, currency exchange rates, joint ventures and investments. We develop a model that optimizes plant investment decisions, while ensuring that the plant investment overhead is optimally absorbed by products produced from that plant. The model also, simultaneously, determines prices by products and countries. The special structure of the model is exploited to construct a fast solution procedure. The model is used to study the implications of labor cost, transportation cost, demand, and import tariff on production quantities, investment, and overhead absorption pattern. Implications of changes in other global parameters such as local-content rule, local taxes, size of the market in a country, and long-term exchange rates are also studied.