Solving a discrete congested multi-objective location problem by hybrid simulated annealing with customers' perspective.pdf
Creators: name: Seifbarghy, Mehdi
name: M. Ghobadia
name: R. Tavakoli-Moghadam
name: Davar Pishva
Publisher: name: figshare
Year: 2020
Subjects: subject: 90603 Industrial Electronics
subject: FOS: Electrical engineering, electronic engineering, information engineering
subject: FOS: Electrical engineering, electronic engineering, information engineering
subject: 90505 Infrastructure Engineering and Asset Management
subject: FOS: Civil engineering
subject: FOS: Civil engineering
subject: 91599 Interdisciplinary Engineering not elsewhere classified
subject: FOS: Other engineering and technologies
subject: FOS: Other engineering and technologies
subject: 91003 Machine Tools
subject: 91004 Machining
subject: 91099 Manufacturing Engineering not elsewhere classified
subject: 91005 Manufacturing Management
subject: 91006 Manufacturing Processes and Technologies (excl. Textiles)
subject: 91007 Manufacturing Robotics and Mechatronics (excl. Automotive Mechatronics)
subject: 91008 Manufacturing Safety and Quality
subject: 91199 Maritime Engineering not elsewhere classified
subject: FOS: Environmental engineering
subject: FOS: Environmental engineering
subject: 91299 Materials Engineering not elsewhere classified
subject: FOS: Materials engineering
subject: FOS: Materials engineering
subject: Mechanical Engineering
subject: FOS: Mechanical engineering
subject: FOS: Mechanical engineering
subject: 91399 Mechanical Engineering not elsewhere classified
subject: 90304 Medical Devices
subject: FOS: Medical engineering
subject: FOS: Medical engineering
subject: 90404 Membrane and Separation Technologies
subject: FOS: Chemical engineering
subject: FOS: Chemical engineering
subject: 91207 Metals and Alloy Materials
subject: 91306 Microelectromechanical Systems (MEMS)
subject: 90604 Microelectronics and Integrated Circuits
subject: 91009 Microtechnology
subject: 91404 Mineral Processing/Beneficiation
subject: 91405 Mining Engineering
subject: 91102 Naval Architecture
subject: 90904 Navigation and Position Fixing
subject: 90405 Non-automotive Combustion and Fuel Engineering (incl. Alternative/Renewable Fuels)
subject: Nuclear Engineering
subject: 91506 Nuclear Engineering (incl. Fuel Enrichment and Waste Processing and Storage)

description: In the current competitive market, obtaining a greater share of the market requires consideration of the customers' preferences and meticulous demands. This study addresses this issue with a queuing model that uses multi-objective set covering constraints. It considers facilities as potential locations with the objective of covering all customers with a minimum number of facilities. The model is designed based on the assumption that customers can meet their needs by a single facility. It also considers three objective functions, namely minimizing the total number of the assigned server, minimizing the total transportation and facility deployment costs, and maximizing the quality of service from the customers' point of view. The main constraint is that every center should have less than b numbers of people in line with a probability of at least α upon the arrival of a new customer. The feasibility of the approach is demonstrated by several examples which are designed and optimized by a proposed hybrid Simulated Annealing (SA) algorithm to evaluate the model's validity. Finally, the study compares the performance of the proposed algorithm with that of Variable Neighborhood Search (VNS) algorithm and concludes that it can arrive at an optimal solution in much less time than the VNS algorithm. © 2016 Sharif University of Technology.