IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Hub Location Allocation Problems and Solution Algorithms

Hub Location Allocation Problems and Solution Algorithms
View Sample PDF
Author(s): Peiman A. Sarvari (Istanbul Technical University, Turkey), Fatma Betül Yeni (Istanbul Technical University, Turkey) and Emre Çevikcan (Istanbul Technical University, Turkey)
Copyright: 2018
Pages: 30
Source title: Handbook of Research on Applied Optimization Methodologies in Manufacturing Systems
Source Author(s)/Editor(s): Ömer Faruk Yılmaz (Istanbul Technical University, Turkey & Yalova University, Turkey) and Süleyman Tüfekçí (University of Florida, USA)
DOI: 10.4018/978-1-5225-2944-6.ch005

Purchase

View Hub Location Allocation Problems and Solution Algorithms on the publisher's website for pricing and purchasing information.

Abstract

The Hub Location-Allocation Problem is one of the most important topics in industrial engineering and operations research, which aims to find a form of distribution strategy for goods, services, and information. There are plenty of applications for hub location problem, such as Transportation Management, Urban Management, locating service centers, Instrumentation Engineering, design of sensor networks, Computer Engineering, design of computer networks, Communication Networks Design, Power Engineering, localization of repair centers, maintenance and monitoring power lines, and Design of Manufacturing Systems. In order to define the hub location problem, the present chapter offers two different metaheuristic algorithms, namely Particle Swarm Optimization or PSO and Differential Evolution. The presented algorithms, then, are applied to one of the hub location problems. Finally, the performances of the given algorithms are compared in term of benchmarking.

Related Content

Scheduling in Flexible Manufacturing Systems: Genetic Algorithms Approach
Fraj Naifar, Mariem Gzara, Taicir Loukil Moalla. © 2018. 19 pages.
View Details View Details PDF Full Text View Sample PDF
Application and Evaluation of Bee-Based Algorithms in Scheduling: A Case Study on Project Scheduling
Ayse Aycim Selam, Ercan Oztemel. © 2018. 23 pages.
View Details View Details PDF Full Text View Sample PDF
Metaheuristic Approaches for Extrusion Manufacturing Process: Utilization of Flower Pollination Algorithm and Particle Swarm Optimization
Pauline Ong, Desmond Daniel Vui Sheng Chin, Choon Sin Ho, Chuan Huat Ng. © 2018. 14 pages.
View Details View Details PDF Full Text View Sample PDF
A Heuristic Approach for Car Sequencing Problem Including Assembly Ratio and Color Constraints
Emek Gamze Köksoy Atiker, Fatma Betül Yeni, Peiman A. Sarvari, Emre Çevikcan. © 2018. 20 pages.
View Details View Details PDF Full Text View Sample PDF
Hub Location Allocation Problems and Solution Algorithms
Peiman A. Sarvari, Fatma Betül Yeni, Emre Çevikcan. © 2018. 30 pages.
View Details View Details PDF Full Text View Sample PDF
Heuristic Approaches in Clustering Problems
Onur Doğan. © 2018. 18 pages.
View Details View Details PDF Full Text View Sample PDF
An Integrated Methodology for Order Release and Scheduling in Hybrid Manufacturing Systems: Considering Worker Assignment and Utility Workers
Ömer Faruk Yılmaz, Mehmet Bülent Durmuşoğlu. © 2018. 37 pages.
View Details View Details PDF Full Text View Sample PDF
Body Bottom