Optimization of facility location problem in reverse logistics network using Artificial Bee Colony algorithm

2013 ◽  
Author(s):  
S. Z. Zhang ◽  
C. K. M. Lee
Keyword(s):  
Facility Location ◽  
Reverse Logistics ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Location Problem ◽  
Facility Location Problem ◽  
Logistics Network ◽  
Bee Colony ◽  
Reverse Logistics Network

A hybrid artificial bee colony for optimizing a reverse logistics network system

2017 ◽  
Vol 21 (20) ◽  
pp. 6001-6018 ◽  
Author(s):  
Jun-qing Li ◽  
Ji-dong Wang ◽  
Quan-ke Pan ◽  
Pei-yong Duan ◽  
Hong-yan Sang ◽  
...  
Keyword(s):  
Reverse Logistics ◽  
Artificial Bee Colony ◽  
Network System ◽  
Logistics Network ◽  
Bee Colony ◽  
Reverse Logistics Network

Reverse Logistics Network Design for the Collection of End-of-Life Vehicles

2012 ◽  
Author(s):  
Hang Dai ◽  
Qing Wang
Keyword(s):  
Network Design ◽  
End Of Life ◽  
Facility Location ◽  
Reverse Logistics ◽  
Location Problem ◽  
Strategic Decision ◽  
Mixed Integer ◽  
Logistics Network ◽  
Reverse Logistics Network ◽  
Reverse Logistic

Reverse logistic network design problems involve strategic decisions which influence tactical and operational decisions. In particular, they involve facility location, transportation and inventory decisions, which affect the cost of the distribution system and the quality of the customer service level. Locating a collection centre is an important strategic decision, as purchasing or building facilities requires sizable investment; also the network transportation cost is affected by the selection of facility locations. The location that is selected must therefore take into account all the parameters and variables that are relevant and the decision may even affect demand. In this paper, network design for reverse logistics is investigated to solve the End-of-life Vehicles (ELV) collection centres location problem. We start by giving an understanding of the process of this reverse logistics network design by considering the features of reverse logistics, the role of ELV management and use of optimization methods. Based on this, a reverse logistics network design case for collection of End-of-life Vehicles is presented by formulating the problem into a mixed-integer linear program (MILP), taking into consideration the Capacitated Facility Location Problem. The solution to this model is obtained using IBM CPLEX Optimization Studio©. In addition the applicability of the model in other reverse logistic networks is discussed and the subjects for further research are pointed out.

Clustering Approach Using Artificial Bee Colony Algorithm for Healthcare Waste Disposal Facility Location Problem

2019 ◽  
Vol 10 (1) ◽  
pp. 56-75 ◽  
Author(s):  
Zeynep Gergin ◽  
Nükhet Tunçbilek ◽  
Şakir Esnaf
Keyword(s):  
Facility Location ◽  
Waste Disposal ◽  
Real World ◽  
Artificial Bee Colony ◽  
Clustering Algorithm ◽  
Location Problem ◽  
Facility Location Problem ◽  
Healthcare Waste ◽  
Bee Colony ◽  
Disposal Facility

In this study, an Artificial Bee Colony (ABC) based clustering algorithm is proposed for solving continuous multiple facility location problems. Unlike the original version applied to multivariate data clustering, the ABC based clustering here solves the two-dimensional clustering. On the other hand, the multiple facility location problem the proposed clustering algorithm deals with is aimed to find site locations for healthcare wastes. After applying ABC based clustering algorithm on test data, a real-world facility location problem is solved for identifying healthcare waste disposal facility locations for Istanbul Municipality. Geographical coordinates and healthcare waste amounts of Istanbul hospitals are used to decide the locations of sterilization facilities to be established for reducing the medical waste generated. ABC based clustering is performed for different number of clusters predefined by Istanbul Metropolitan Municipality, and the total cost—the amount of healthcare waste produced by a hospital, multiplied by its distance to the sterilization facility—is calculated to decide the number of facilities to be opened. Benchmark results with four algorithms for test data and with two algorithms for real world problem reveal the superior performance of the proposed methodology.

scholarly journals Robust facility location in reverse logistics

2021 ◽  
Author(s):  
Péter Egri ◽  
Balázs Dávid ◽  
Tamás Kis ◽  
Miklós Krész
Keyword(s):  
Facility Location ◽  
Reverse Logistics ◽  
Economies Of Scale ◽  
Real Life ◽  
Facility Location Problem ◽  
Bilevel Optimization ◽  
Logistics Network ◽  
Final Destination ◽  
Novel Approach ◽  
Tabu Search Method

AbstractAs environmental awareness is becoming increasingly important, alternatives are needed for the traditional forward product flows of supply chains. The field of reverse logistics covers activities that aim to recover resources from their final destination, and acts as the foundation of the efficient backward flow of these materials. Designing the appropriate reverse logistics network for a given field is a crucial problem, as this provides the basis for all operations connected to the resource flow. This paper focuses on design questions in the supply network of waste wood, dealing with its collection and transportation to designated processing facilities. The facility location problem is studied for this use-case, and mathematical models are developed that consider economies of scale and the robustness of the problem. A novel approach based on bilevel optimization is used for computing the exact solutions of the robust problem on smaller instances. A local search and a tabu search method is also introduced for solving problems of realistic sizes. The developed models and methods are tested both on real-life and artificial instance sets in order to assess their performance.

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