Mr. Mohammad Rohaninejad, Dr. Amirhossein Amiri, Dr. Mahdi Bashiri,
Volume 26, Issue 3 (9-2015)
Abstract
This paper addresses a reliable facility location problem with considering facility capacity constraints. In reliable facility location problem some facilities may become unavailable from time to time. If a facility fails, its clients should refer to other facilities by paying the cost of retransfer to these facilities. Hence, the fail of facilities leads to disruptions in facility location decisions and this problem is an attempt to reducing the impact of these disruptions. In order to formulate the problem, a new mixed-integer nonlinear programming (MINLP) model with the objective of minimizing total investment and operational costs is presented. Due to complexity of MINLP model, two different heuristic procedures based on mathematical model are developed. Finally, the performance of the proposed heuristic methods is evaluated through executive numerical example. The numerical results show that the proposed heuristic methods are efficient and provide suitable solutions.
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Mohammad Mahdi Nasiri, Nafiseh Shamsi Gamchi, Seyed Ali Torabi,
Volume 27, Issue 4 (12-2016)
Abstract
Hubs are critical elements of transportation networks. Location of hubs and allocation of demands to them are of high importance in the network design. The most important purpose of these models is to minimize the cost, but path reliability is also another important factor which can influence the location of hubs. In this paper, we propose a P-center hub location model with full interconnection among hubs while there are different paths between origins and destinations. The purpose of the model is to determine the reliable path with lower cost. Unlike the prior studies, the number of hubs in the path is not limited to two hubs. The presented model in this paper is bi-objective and includes cost and reliability to determine the best locations for hubs, allocation of the demands to hubs and the best path. In order to illustrate our model, a numerical example is presented and solved using the Cuckoo Optimization Algorithm.
Dr. Zahra Esfandiari, Prof. Mahdi Bashiri, Prof. Reza Tavakkoli-Moghaddam,
Volume 31, Issue 1 (3-2020)
Abstract
One of the major risks that can affect supply chain design and management is the risk of facility disruption due to natural hazards, economic crises, terrorist attacks, etc. Static resiliency of the network is one of the features that is considered when designing networks to manage disruptions, which increases the network reliability. This feature refers to the ability of the network to maintain its operation and connection in the lack of some members of the chain. Facility hardening is one of the strategies used for this purpose. In this paper, different reliable capacitated fixed-charge location allocation models are developed for hedging network from failure. In these proposed models, hardening, resilience, and hardening and resilience abilities are considered respectively. These problems are formulated as a nonlinear programming models and their equivalent linear form are presented. The sensitivity analysis confirms that the proposed models construct more effective and reliable network comparing to the previous networks. A Lagrangian decomposition algorithm (LDA) is developed to solve the linear models. Computational results show that the LDA is efficient in computational time and quality of generated solutions for instances with different sizes. Moreover, the superiority of the proposed model is confirmed comparing to the classical model.
