Improved Adaptive Differential Evolution Algorithm for the Un-Capacitated Facility Location Problem

The differential evolution algorithm is an evolutionary algorithm for global optimization and the un-capacitated facility location problem (UFL) is one of the classic NP-Hard problems. In this paper, combined with the specific characteristics of the UFL problem, we introduce the activation function to the algorithm for solving UFL problem and name it improved adaptive differential evolution algorithm (IADEA). Next, to improve the efficiency of the algorithm and to alleviate the problem of being stuck in a local optimum, an adaptive operator was added. To test the improvement of our algorithm, we compare the IADEA with the basic differential evolution algorithm by solving typical instances of UFL problem respectively. Moreover, to compare with other heuristic algorithm, we use the hybrid ant colony algorithm to solve the same instances. The computational results show that IADEA improves the performance of the basic DE and it outperforms the hybrid ant colony algorithm.

Approximation Algorithms for the Priority Facility Location Problem with Penalties

develop a mentation This paper considers the priority facility primal-dual 3-approximation algorithm for procedure, the authors further improve the location problem with penalties： The authors this problem. Combining with the greedy aug- previous ratio 3 to 1.8526.

Reliability Analysis of Facility Systems Subject to Edge Failures: Based on the Uncapacitated Fixed-Charge Location Problem

A facility system can be modeled by a connected graph in which the vertices represent entities such as suppliers, distribution centers or customers and the edges represent facilities such as the paths of goods or information. The efficiency, and hence the reliability, of a facility system is to a large degree adversely affected by the edge failures in the network. Such failures may be caused by various natural disasters or terrorist attacks. In this paper, we consider facility systems’ reliability analysis based on the classical uncapacitated fixed-charge location problem when subject to edge failures. For an existing facility system, we formulate two models based on deterministic case and stochastic case to measure the loss in efficiency due to edge failures and give computational results and reliability envelopes for a specific example.

Reliable Facility Systems Design Subject to Edge Failures: Based on the Uncapacitated Fixed-Charge Location Problem

The reliability of facility location problem has aroused wide concern recently. Many researchers focus on reliable and robust facility systems design under component failures and have obtained promising performance. However, the target and reliability of a facility system are to a large degree adversely affected by the edge failures in the network, which remains a deep study. In this paper, we focus on facility systems’ reliability subject to edge failures. For a facility location system, we formulate two models based on classical uncapacitated fixed-charge location problem under deterministic and stochastic cases. For a specific example, location decisions and the comparison of reliability under different location models are given. Extensive experiments verify that significant improvements in reliability can be attained simply by increasing the amount of operating cost.

Implementing Lagrangean Decomposition Technique to Acquire an Adequate Lower Boundon the Facility Location Problem Solution

In this work, the Lagrangean Relaxation method has been discussed to solve different sizes of capacitated facility location problem (CFLP). A good lower bound has been achieved on the solution of the CFLP considered in this paper. This lower bound has been improved by using the Volume algorithm. The methods of setting two important parameters in heuristic have been given. The approaches used to gain the lower bound have been explained. The results of this work have been compared with the known results given by Beasley.

A Multi-Objective Obnoxious Facility Location Modelon a Plane

In this paper a Vertex Covering Obnoxious Facility Location model on a Plane has been designed with a combination of three interacting criteria as follows: 1) Minimize the overall importance of the various exist-ing facility points;2) Maximize the minimum distance from the facility to be located to the existing facility points;3) Maximize the number of existing facility points covered. Area restriction concept has been incor-porated so that the facility to be located should be within certain restricted area. The model developed here is a class of maximal covering problem, that is covering maximum number of points where the facility is within the upper bounds of the corresponding mth feasible region Two types of compromise solution methods have been designed to get a satisfactory solution of the multi-objective problem. A transformed non- linear programming algorithm has been designed for the proposed non-linear model. Rectilinear dis-tance norm has been considered as the distance measure as it is more appropriate to various realistic situa-tions. A numerical example has been presented to illustrate the solution algorithm.

An Algorithm for Solving Generalized Single Row Facility Layout Problem

Layout design problem is to determine a suitable arrangement for the departments so that the total costs associated with the flow among departments become least. Single Row Facility Layout Problem, SRFLP, is one of the layout problems that have many practical applications. This problem and its specific scenarios are often used to model many of the raised issues in the field of facility location. SRFLP is an arrangement of n departments with a specified length in a straight line so that the sum of the weighted distances between the pairs of departments is minimized. This problem is NP-hard. In this paper, first, a lower bound for a special case of SRFLP is presented. Then, a general case of SRFLP is presented in which some new and real assumptions are added to generate more practical model. Then a lower bound, as well as an algorithm, is proposed for solving the model. Experimental results on some instances in literature show the efficiency of our algorithm.

Research on Location-Routing Problem with Empirical Analysis for Regional Logistics Distribution

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.

Reliability Analysis of Systems Based on the UFLP under Facility Failure and Conditional Supply Cases

The reliability of facility location problems has been received wide attention for several decades. Researchers formulate varied models to optimize the reliability of location decisions. But the most of such studies are not practical since the models are too ideal. In this paper, based on the classical uncapacitated fixed-charge location problem (UFLP) and some supply constraints from the reality, we distinguish deterministic facility failure and stochastic facility failure cases to formulate models to measure the reliability of a system. The computational results and reliability envelopes for a specific example are also given.

An Approximation Algorithm for the Dynamic Facility Location Problem with Submodular Penalties

In this paper, we study the dynamic facility location problem with submodular penalties （DFLPSP）. We present a combinatorial primal-dual 3-approximation algorithm for the DFLPSP.

Fault-tolerant Concave Facility Location Problem with Uniform Requirements

In this paper, we consider the fault-tolerant concave facility location problem （FTCFL） with uniform requirements. By investigating the structure of the FTCFL, we obtain a modified dual-fitting bifactor approximation algorithm. Combining the scaling and greedy argumentation technique, the approximation factor is proved to be 1.52.

An improved per-scenario bound for the two-stage stochastic facility location problem

We study the two-stage stochastic facility location problem(2-SFLP)by proposing an LP(location problem)-rounding approximation algorithm with 2.3613 per-scenario bound for this problem,improving the previously best per-scenario bound of 2.4957.

An Approximation Algorithm for the Stochastic Fault-Tolerant Facility Location Problem

In this paper,we study a stochastic version of the fault-tolerant facility location problem.By exploiting the stochastic structure,we propose a 5-approximation algorithm which uses the LP-rounding technique based on the revised optimal solution to the linear programming relaxation of the stochastic fault-tolerant facility location problem.

考虑设施规模决策的两级选址-路径优化

针对目前电商行业基础设施布局和空间利用不合理的问题,提出考虑设施规模决策的两级选址-路径问题(2E-LRP)求解模型。首先,在传统2E-LRP中引入差异性设施规模约束,通过识别客户群设计不同设施规模组合,利用规模弹性变化调整总成本组成,并以最小运营成本为目标建立顾及设施规模弹性变化的2E-LRP模型;其次,提出两阶段混合迭代局部搜索启发式算法求解模型;最后,分析所提模型和优化算法,并以Prodhon等不同数据集为实例进行验证。实验结果表明,所提模型具有针对区域差异和不同数据规模的普适性,且设施规模的弹性变化范围值与总成本呈负相关;与拉格朗日松弛粒度禁忌搜索(LRGTS)等算法的最优成本相比,所提算法对所有算例的最优成本平均值降低了6.67%,可以有效节约运行成本。

基于改进多目标遗传算法的电动汽车换电站选址研究

换电模式高效、便捷的补能形式预计成为未来电动汽车充能的主流方式。换电站选址是否合理影响重大,本文以换电站建设成本及用户出行成本最小化、用户覆盖率最大化为目标函数,建立双目标混合整数规划模型,设计改进带精英策略的非支配排序遗传算法,获得帕累托最优解集。通过数值模拟,验证了模型可行性,为电动汽车换电站网络规划提供了依据。

具有设施容量选择的两阶段设施选址问题研究

设施位置与设施容量是影响供应链长期运营成本和服务质量的重要因素,也是企业获得竞争优势的两个决定性因素。针对设施选址及容量选择优化问题,本文提出以最小化成本为目标的混合整数规划模型,对工厂和仓库的位置及容量,工厂到仓库的产品流和客户到仓库的分配进行优化。根据模型特点设计拉格朗日松弛算法对其进行求解,为了提高解的质量,本文开发混合模拟退火禁忌搜索算法对拉格朗日松弛算法的求解结果进行改进。本文利用随机生成的大量具有不同规模及参数的实例对算法的有效性进行检验,数值实验表明该算法适用于同时优化设施选址及容量选择问题。

基于时间满意的最大覆盖选址问题

传统的选址问题过于简单地考量时间这一对企业竞争力影响重大的因素,结合这一特点,本文对时间满意度函数进行了定义并提出了基于时间满意的最大覆盖选址问题。给定的网络G(V,A)中,在总的顾客对服务站响应速度的满意程度最大的目标下建立了最大覆盖选址问题模型,我们在讨论了问题的特点之后给出了基于拉格朗日松驰的启发式算法,并通过MATLAB进行了编程计算实验,分析了实验结果。

集成物流管理系统中定位—运输路线安排问题的研究

综述集成物流管理系统中设施定位—运输车辆行程路线安排问题的主要研究进展 ,分析提出有关求解问题的算法的特点 ,最后提出该研究领域应该关注的几个重要发展方向 .

考虑设施失效的军事物流配送中心选址模型

为了提高军事配送系统的经济性,针对物资配送中后勤设施失效时进行支援保障和越级保障的情况,将军事物流配送中心的属性分为"首选"与"备选"两种,并把设施失效时的应急配送成本作为决策目标的一部分,建立了最小化设施固定成本、正常配送成本、应急配送成本之和的军事物流配送中心选址模型,采用贪婪取走的启发式算法进行了模型求解,比较了考虑设施失效情况的选址方案与未考虑设施失效情况的选址方案之间的差别。仿真算例结果表明,虽然由模型所得选址方案的设施固定成本与正常配送成本之和高于未考虑设施失效情况的选址方案,但平均期望成本增加值低于后者。

考虑设施中断情景的震后救援初期应急物流网络优化设计

在震后救援初期,构建合理的应急物流网络,对于快速有效供应应急物资、减轻灾情具有重大价值。在传统可靠性选址问题与应急设施选址-分配问题的基础上,考虑震后救援初期的阶段性特征、设施中断情景、多品种模糊需求、设施能力限制等因素,建立了一个适用于震后救援初期的应急设施选址-分配模型。通过三角模糊数的期望值公式将模糊需求去模糊化。在此基础上,考虑模型特点,设计了一种整数编码的混合遗传算法。最后,以5·12汶川地震为背景,构造算例进行数值仿真。验证了所提模型和算法。结果表明:考虑设施中断情景后,即使系统中的部分设施失效,整个网络仍能较好运行,且优化结果更具可靠性和稳健性。