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Hasanzadeh, A. ,
Afshari, H. ,
Kianfar, K. ,
Fathi, M. ,
Jadid, A.O. Publication Date: 2009
pp. 1930-1934
In this paper, a metaheuristic approach for the two-machine flow-shop problem with a common due date and the weighted late work performance measure (F2|dj=d|Yw) are presented. The late work criterion estimates the quality of a solution with regard to the duration of the late parts of jobs, not taking into account the quantity of the delay for the fully late activities. Since the problem mentioned is known to be NP-hard, a trajectory methods, namely GRASP is proposed based on the special features of the case under consideration. Then, the results of computational experiments are reported, in which the metaheuristic solution is compared with exact approach and three other heuristic methods' results. ©2009 IEEE.
Publication Date: 2009
Computers and Operations Research (03050548) 36(8)pp. 2450-2461
In this paper, steel-making continuous casting (SCC) scheduling problem (SCCSP) is investigated. This problem is a specific case of hybrid flow shop scheduling problem accompanied by technological constraints of steel-making. Since classic optimization methods fail to obtain an optimal solution for this problem over a suitable time, a novel iterative algorithm is developed. The proposed algorithm, named HANO, is based on a combination of ant colony optimization (ACO) and non-linear optimization methods. The solution construction in HANO is broken up into two phases. The first phase determines the discrete variables (corresponding to job-machine assignment and sequencing), while the second phase determines the continuous ones (corresponding to timing of the jobs on their assigned machines) through a non-linear optimization method. The efficiency of HANO is compared with a heuristic algorithm as a real case used at Mobarakeh Steel Company (MSC), the biggest steel factory in the Middle East. In addition, the proposed algorithm is compared with Genetic Algorithm, as a search method for both discrete and continuous variables, through solving several instances. Numerical results reveal the higher efficiency of the proposed approach compared with the heuristic one used at MSC. Furthermore, the efficiency of HANO is compared with GA to show that HANO enjoys a better performance in more than 95% of the cases while in the remaining 5%, its performance efficiency shows no difference. © 2008 Elsevier Ltd. All rights reserved.
Publication Date: 2009
pp. 1253-1257
This work is concerned with customer-oriented catalog segmentation that each catalog consists of specific number of products. In this problem, requirements of a specific ratio of customers should be satisfied. According to the definition, when a customer is satisfied that at least t required products exist in his/her catalog. The objective of this problem is to minimize the number of catalogs, regarding to minimum number of customers constraint that was comply. In this paper, we present a mixed-integer programming model for this clustering problem. This problem is NP-Hard in large scales and the optimum solution is almost impossible to reach. Hence, a solution procedure is developed based on genetic algorithm. Then, the results of computational experiments are reported, in which the GA solution is compared with exact solution of mixed-integer programming model. ©2009 IEEE.
Publication Date: 2009
pp. 1234-1238
This work is concerned with the fuzzy clustering problem of different products in k variant catalogs, each of size r products that maximize customer satisfaction level in customer relationship management (CRM). The satisfaction degree of each customer is defined as a function of his/her needed product number that exists in catalog and also his/her priority. To determine the priority level of each customer, firstly customers are divided to three clusters with high, medium and low importance based on his/her needed products list. Then, all customers have been ranked based on their membership level in each of the above three clusters. In this paper in order to cluster customers, fuzzy c-means algorithm is applied. The proposed problem is firstly modeled as a bi-objective mathematical programming model. The objective functions of the model are to maximize the number of covered customers and overall satisfaction level results of delivering service. Then, this model is changed to a single integer linear programming model by applying fuzzy theory concepts. Finally, the efficiency of the proposed solution procedure is verified by using a numerical example. ©2009 IEEE.
Publication Date: 2009
Journal Of Intelligent Manufacturing (15728145) 20(4)pp. 347-357
This paper presents a novel approach to the facility layout design problem based on multi-agent society where agents' interactions form the facility layout design. Each agent corresponds to a facility with inherent characteristics, emotions, and a certain amount of money, forming its utility function. An agent's money is adjusted during the learning period by a manager agent while each agent tries to tune the parameters of its utility function in such a way that its total layout cost can be minimized in competition with others. The agents' interactions are formed based on market mechanism. In each step, an unoccupied location is presented to all applicant agents, for which each agent proposes a price proportionate to its utility function. The agent proposing a higher price is selected as the winner and assigned to that location by an appropriate space-filling curve. The proposed method utilizes the fuzzy theory to establish each agent's utility function. In addition, it provides a simulation environment using an evolutionary algorithm to form different interactions among the agents and makes it possible for them to experience various strategies. The experimental results show that the proposed approach achieves a lower total layout cost compared with state of the art methods. © 2008 Springer Science+Business Media, LLC.
Publication Date: 2009
International Journal of Advanced Manufacturing Technology (02683768) 45(7-8)pp. 759-771
This paper studies a flexible flow shop system considering dynamic arrival of jobs and the ability of acceptance and rejection of new jobs. The problem objective is to determine a schedule that minimizes sum of the tardiness and rejection costs of jobs. A 0-1 mixed integer model of the problem is formulated. Since this problem class is NP-hard, four dispatching rules have been developed to solve the problem approximately. Moreover, a discrete event simulation model of the flexible flow shop system is developed for the purpose of experimentation. Four dispatching rules from the literature and four new dispatching rules proposed in this paper are incorporated in the simulation model. Simulation experiments have been conducted under various experimental conditions characterized by factors such as shop utilization level, due date tightness and number of stages in flexible flow shop. The results indicate that proposed dispatching rules provide better performance under problem assumptions. © 2009 Springer-Verlag London Limited.
Zadeh, A.H. ,
Maleki, H. ,
Kianfar, K. ,
Fathi, M. ,
Zaeri, M.S. Publication Date: 2010
Advances in Intelligent and Soft Computing (18675670) 73pp. 161-169
This work is concerned with the fuzzy clustering problem of different products in j variant catalogs, each of size i products that maximize customer satisfaction level in customer relationship management. The satisfaction degree of each customer is defined as a function of his/her needed product number that exists in catalog and also his/her priority. To determine the priority level of each customer, firstly customers are divided to three clusters with high, medium and low importance based on his/her needed products list. Then, all customers have been ranked based on their membership level in each of the above three clusters. In this paper in order to cluster customers, fuzzy c-means algorithm is applied. The proposed problem is firstly modeled as a bi-objective mathematical programming model. The objective functions of the model are to maximize the number of covered customers and overall satisfaction level results of delivering service. Then, this model is changed to a single integer linear programming model by applying fuzzy theory concepts. Finally, the efficiency of the proposed solution procedure is verified by using a numerical example. © Springer-Verlag Berlin Heidelberg 2010.
Publication Date: 2010
International Journal of Advanced Manufacturing Technology (02683768) 47(1-4)pp. 269-281
Reverse logistics is becoming more important in overall industry area because of the environmental and business factors. Planning and implementing a suitable reverse logistics network could bring more profit, customer satisfaction, and a nice social picture for companies. But, most of logistics networks are not equipped to handle the return products in reverse channels. This paper proposes a mixed integer linear programming model to minimize the transportation and fixed opening costs in a multistage reverse logistics network. Since such network design problems belong to the class of NP-hard problems, we apply a simulated annealing (SA) algorithm with special neighborhood search mechanisms to find the near optimal solution. We also compare the associated numerical results through exact solutions in a set of problems to present the high-quality performance of the applied SA algorithm. © 2009 Springer-Verlag London Limited.
Publication Date: 2012
Computers and Operations Research (03050548) 39(12)pp. 2978-2990
This paper considers the problem of scheduling a single machine, in which the objective function is to minimize the weighted quadratic earliness and tardiness penalties and no machine idle time is allowed. We develop a branch and bound algorithm involving the implementation of lower and upper bounding procedures as well as some dominance rules. The lower bound is designed based on a lagrangian relaxation method and the upper bound includes two phases, one for constructing initial schedules and the other for improving them. Computational experiments on a set of randomly generated instances show that one of the proposed heuristics, used as an upper bound, has an average gap less than 1.3% for instances optimally solved. The results indicate that both the lower and upper bounds are very tight and the branch-and-bound algorithm is the first algorithm that is able to optimally solve problems with up to 30 jobs in a reasonable amount of time. © 2012 Elsevier Ltd. All rights reserved.
Publication Date: 2012
Advances in Operations Research (16879155) 2012
Operating room scheduling is an important operational problem in most hospitals. In this paper, a novel mixed integer programming (MIP) model is presented for minimizing Cmax and operating room idle times in hospitals. Using this model, we can determine the allocation of resources including operating rooms, surgeons, and assistant surgeons to surgeries, moreover the sequence of surgeries within operating rooms and the start time of them. The main features of the model will include the chronologic curriculum plan for training residents and the real-life constraints to be observed in teaching hospitals. The proposed model is evaluated against some real-life problems, by comparing the schedule obtained from the model and the one currently developed by the hospital staff. Numerical results indicate the efficiency of the proposed model compared to the real-life hospital scheduling, and the gap evaluations for the instances show that the results are generally satisfactory. Copyright © 2012 Somayeh Ghazalbash et al.
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