A facility location model for logistics systems including reverse flows: The case of remanufacturing activities

After a brief introduction to the basic concepts of reverse logistics, we present a two-level location problem with three types of facility to be located in a specific reverse logistics system, named a Remanufacturing Network (RMN). For this problem, we propose a 0–1 mixed integer programming model, in which we simultaneously consider “forward” and “reverse” flows and their mutual interactions. An algorithm based on Lagrangian heuristics is developed and the model is tested on data adapted from classical test problems.     

A Lagrangian relaxation approach for a large scale new variant of capacitated clustering problem

This paper studies a new variant of capacitated clustering problem (VCCP). In the VCCP, p facilities which procure a raw material from a set of suppliers are to be located among n potential sites (n > p) such that the total cost of assigning suppliers to the facilities and opening such facilities is minimized. Each supplier has a limited supply volume and each facility has a minimum supply requirement that must be satisfied by assigning enough suppliers to the facility. Each supplier can be assigned to at most one facility. When a supplier is assigned to a facility, the former will supply its all available volume to the latter. In order to solve the VCCP, a Lagrangian relaxation approach (LR) with two phases of dual optimization, the subgradient deflection in the first phase and the standard subgradient method in the second phase, is proposed. In the approach, the assignment constraints are relaxed. The resulting Lagrangian relaxed problem can be decomposed into a set of independent knapsack problems, which can be solved to optimality efficiently. At each Lagrangian iteration, a feasible solution is constructed from that of the Lagrangian relaxed problem by applying a greedy algorithm. Finally, the best feasible solution found so far is improved by a simple tabu search algorithm. Numerical tests on random instances show that the proposed LR can produce a tight lower bound and a high quality feasible solution for all instances with up to 4000 suppliers, 200 potential sites, and 100 plants to locate.     

Unresolved Issues in Supply Chain Network Design

Designing a supply chain network provides the basic structure for supply chain operations, where the network is a major element in a firm's competitiveness and a significant area of capital investment. With the boundary-spanning scope encouraged by supply chain management, the question is whether existing analyses used for network design are adequate. The general answer is yes, because the number of echelons that the analysis must span is self-limiting to a relative few. However, there remain unresolved issues in network design analysis and in the models used to support the analysis that can enhance its accuracy, appropriateness, and acceptability to practitioners. Issues discussed relate to the development of better models, the treatment of the data needed by them, and the need for comparing the various models for network design.     

浅谈计算机网络技术对物流信息化的影响

随着科学技术的进一步发展,我国计算机网络的发展前景喜人,为物流业实现信息化奠定了坚实的基础。物流信息化建设的不断推进,为建立物流业低成本、快捷、高效的配送体系提供了广阔的空间。本文主要分析了计算机网络技术在物流信息化建设中的作用,并阐明了其对物流信息化建设的突出影响,并以此为基础,进一步保证物流业的信息安全。     

Solving continuous location–districting problems with Voronoi diagrams

Facility location problems are frequent in OR literature. In districting problems, on the other hand, the aim is to partition a territory into smaller units, called districts or zones, while an objective function is optimized and some constraints are satisfied, such as balance, contiguity, and compactness. Although many location and districting problems have been treated by assuming the region previously partitioned into a large number of elemental areas and further aggregating these units into districts with the aid of a mathematical programming model, continuous approximation, on the other hand, is based on the spatial density of demand, rather than on precise information on every elementary unit. Voronoi diagrams can be successfully used in association with continuous approximation models to solve location–districting problems, specially transportation and logistics applications. We discuss in the paper the context in which approximation algorithms can be used to solve this kind of problem.     

Toward perpetually organized unit-load warehouses

Determining the optimal storage assignment for loads in a unit-load warehouse has been extensively addressed in the facility logistics literature. However, the process of implementing a particular storage assignment given the current assignment of loads has not received much attention. Typically, unit-load warehouses use downtime or overtime to remove loads from their current location and move them to the suggested location. This study presents Rearrange-While-Working (RWW) as a strategy to optimize the process of rearranging a warehouse while serving a list of move requests. This study examines three scenarios: (1) one empty location in the warehouse and the material handling equipment (MHE) is idle; (2) one empty location in the warehouse under the RWW strategy; and (3) when there are multiple empty locations in the warehouse under RWW. In the first scenario, the MHE can make any movement desired as it is idle. For the other two scenarios it is assumed that the MHE is not idle so loads can only be moved when requested to perform a move request. Due to the complexity of the problems, several heuristics are proposed. Experimental results indicate that the proposed heuristics perform satisfactorily in terms of solution quality and computational time.     

需求与物流网络不确定下的应急救援选址问题

针对应急物流中需求与物流网络的不确定性特征,对应急救援中应急需求和物流网络均不确定条件下的应急配送中心选址问题进行研究,以成本最小化为目标,建立基于集合覆盖的应急救援设施选址的随机规划模型,采用期望值法和随机模拟两种方法处理数学模型中的不确定性。通过算例与仿真研究,获得应急救援下的配送中心选址最优方案。结果表明,相对于传统的期望值方法处理随机参数,随机模拟方法具有较明显优势。     

A genetic algorithm approach for location-inventory-routing problem with perishable products

In this paper, we address a location-inventory-routing model for perishable products. The model determines the number and location of required warehouses, the inventory level at each retailer, and the routes traveled by each vehicle. The proposed model adds location decisions to a recently published inventory routing problem in order to make it more practical, thus supporting the prevalent claim that integration of strategic, tactical and operational level decisions produces better results for supply chains. Given that the model developed here is NP-hard, with no algorithm capable of finding its solution in polynomial time, we develop a Genetic Algorithm approach to solve the problem efficiently. This approach achieves high quality near-optimal solutions in reasonable time. Furthermore, the unique structure of the problem requires developing a new chromosome representation, as well as local search heuristics. Finally, an analysis is carried out to verify the effectiveness of the algorithm.     

A hub location inventory model for bicycle sharing system design: Formulation and solution

This study addresses a strategic design problem for bicycle sharing systems incorporating bicycle stock considerations. The problem is formulated as a hub location inventory model. The key design decisions considered are: the number and locations of bicycle stations in the system, the creation of bicycle lanes between bicycle stations, the selection of paths of users between origins and destinations, and the inventory levels of sharing bicycles to be held at the bicycle stations. The design decisions are made with consideration for both total cost and service levels (measured both by the availability rate for rental requests at the pick-up rental stations and coverage of the origins and destinations). The optimal design of this system requires an integrated view of the travel costs of users, bicycle inventory costs and facility costs of bicycle stations and bicycle lanes as well as service levels. The purpose of this study is to create a formal model that provides such an integrated view, and to develop methods for obtaining solutions for the design variables in practical situations. The complexity of the problem precludes the exact solution of the optimization problem for instances of realistic size, and so we propose a heuristic method for efficiently finding near-optimal solutions. In the test problem for which enumeration is possible, the heuristic solution is within 2% optimal. Finally, a numerical example is created to illustrate the model and proposed solution algorithm.     

Modeling an international co-operative global complementary production system

This paper aims to design a production planning and control system to realize high productivity and low inventory in the international cooperative global complementary production system for mutual country's development.     

Two-echelon, multi-commodity supply chain network design with mode selection, lead-times and inventory costs

Designing distribution networks - as one of the most important strategic issues in supply chain management - has become the focus of research attention in recent years. This paper deals with a two-echelon supply chain network design problem in deterministic, single-period, multi-commodity contexts. The problem involves both strategic and tactical levels of supply chain planning including locating and sizing manufacturing plants and distribution warehouses, assigning the retailers' demands to the warehouses, and the warehouses to the plants, as well as selecting transportation modes.We have formulated the problem as a mixed integer programming model, which integrates the above mentioned decisions and intends to minimize total costs of the network including transportation, lead-times, and inventory holding costs for products, as well as opening and operating costs for facilities. Moreover, we have developed an efficient Lagrangian based heuristic solution algorithm for solving the real-sized problems in reasonable computational time.     

一种集成化仓储管理系统研究

研究设计了一种面向配送中心和企业的集成化仓储系统，介绍了系统的构成和功能，分析了基于计算杌技术的信息集成管理方法、出入库管理方法、货位分配方法和库存分析管理方法。     

Risk management in uncapacitated facility location models with random demands

In this paper we consider a location-optimization problem where the classical uncapacitated facility location model is recast in a stochastic environment with several risk factors that make demand at each customer site probabilistic and correlated with demands at the other customer sites. Our primary contribution is to introduce a new solution methodology that adopts the mean–variance approach, borrowed from the finance literature, to optimize the “Value-at-Risk” (VaR) measure in a location problem. Specifically, the objective of locating the facilities is to maximize the lower limit of future earnings based on a stated confidence level. We derive a nonlinear integer program whose solution gives the optimal locations for the p facilities under the new objective. We design a branch-and-bound algorithm that utilizes a second-order cone program (SOCP) solver as a subroutine. We also provide computational results that show excellent solution times on small to medium sized problems.     

Emergency facility location under random network damage: Insights from the Istanbul case

Damage to infrastructure, especially to highways and roads, adversely affects accessibility to disaster areas. Predicting accessibility to demand points from the supply points by a systematic model would lead to more effective emergency facility location decisions. To this effect, we model the spatial impact of the disaster on network links by random failures with dependency such that failure of a link induces failure of nearby links that are structurally more vulnerable. For each demand point, a set of alternative paths is generated from each potential supply point so that the shortest surviving path will be used for relief transportation after the disaster. The objective is to maximize the expected demand coverage within a specified distance over all possible network realizations. To overcome the computational difficulty caused by extremely large number of possible outcomes, we propose a tabu search heuristic that evaluates candidate solutions over a sample of network scenarios. The scenario generation algorithm that represents the proposed distance and vulnerability based failure model is the main contribution of our study. The tabu search algorithm is applied to Istanbul earthquake preparedness case with a detailed analysis comparing solutions found in no link failure, independent link failure, and dependent link failure cases. The results show that incorporating dependent link failures to the model improves the covered demand percentages significantly.     

An Approximation Algorithm for a Large-Scale Facility Location Problem

We developed a new practical optimization method that gives approximate solutions for large-scale real instances of the Uncapacitated Facility Location Problem. The optimization consists of two steps: application of the Greedy—Interchange heuristic using a small subset of warehouse candidates, and application of the newly developed heuristic named Balloon Search that takes account of all warehouse candidates, and runs in ( O (3n + 2n log n ) ) expected time (n is the number of nodes of the underlying graph). Our experiments on the spare parts logistics of a Japanese manufacturing company with 6000 customers and 380,000 warehouse candidates led us to conclude that the Greedy heuristic improved the total cost by 9%-11%, that the Interchange heuristic improved the total cost by an additional 0.5%—1.5%, and that Balloon Search improved it by a further 0.5%—1.5%.     

Competitive facility location: the Voronoi game

We consider a competitive facility location problem with two players. Players alternate placing points, one at a time, into the playing arena, until each of them has placed n points. The arena is then subdivided according to the nearest-neighbor rule, and the player whose points control the larger area wins. We present a winning strategy for the second player, where the arena is a circle or a line segment. We permit variations where players can play more than one point at a time, and show that the first player can ensure that the second player wins by an arbitrarily small margin.