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    • List of Articles Javad Rezaeian

      • Open Access Article

        1 - Scheduling of a flexible flow shop with multiprocessor task by a hybrid approach based on genetic and imperialist competitive algorithms
        Javad Rezaeian Hany Seidgar Morteza Kiani
        This paper presents a new mathematical model for a hybrid flow shop scheduling problem with multiprocessor tasks in which sequence dependent set up times and preemption are considered. The objective is to minimize the weighted sum of makespan and maximum tardiness. Thre More
        This paper presents a new mathematical model for a hybrid flow shop scheduling problem with multiprocessor tasks in which sequence dependent set up times and preemption are considered. The objective is to minimize the weighted sum of makespan and maximum tardiness. Three meta-heuristic methods based on genetic algorithm (GA), imperialist competitive algorithm (ICA) and a hybrid approach of GA and ICA are proposed to solve the generated problems. The performances of algorithms are evaluated by computational time and Relative Percentage Deviation (RPD) factors. The results indicate that ICA solves the problems faster than other algorithms and the hybrid algorithm produced best solution based on RPD. Manuscript profile
      • Open Access Article

        2 - Designing an integrated production/distribution and inventory planning model of fixed-life perishable products
        Javad Rezaeian keyvan Shokoufi Sepide Haghayegh Iraj Mahdavi
        This paper aims to investigate the integrated production/distribution and inventory planning for perishable products with fixed life time in the constant condition of storage throughout a two-echelon supply chain by integrating producers and distributors. This problem a More
        This paper aims to investigate the integrated production/distribution and inventory planning for perishable products with fixed life time in the constant condition of storage throughout a two-echelon supply chain by integrating producers and distributors. This problem arises from real environment in which multi-plant with multi-function lines produce multi-perishable products with fixed life time into a lot sizing to be shipped with multi-vehicle to multi-distribution-center to minimize multi-objective such as setup costs between products, holding costs, shortage costs, spoilage costs, transportation costs and production costs. There are many investigations which have been devoted on production/distribution planning area with different assumption. However, this research aims to extend this planning by integrating an inventory system with it in which for each distribution center, net inventory, shortage, FIFO system and spoilage of items are calculated. A mixed integer non-linear programming model (MINLP) is developed for the considered problem. Furthermore, a genetic algorithm (GA) and a simulated annealing (SA) algorithm are proposed to solve the model for real size applications. Also, Taguchi method is applied to optimize parameters of the algorithms. Computational characteristics of the proposed algorithms are examined and tested using t-tests at the 95% confidence level to identify the most effective meta-heuristic algorithm in term of relative percentage deviation (RPD). Finally, Computational results show that the GA outperforms SA although the computation time of SA is smaller than the GA. Manuscript profile
      • Open Access Article

        3 - An Efficient Bi-objective Genetic Algorithm for the Single Batch-Processing Machine Scheduling Problem with Sequence Dependent Family Setup Time and Non-identical Job Sizes
        Javad Rezaeian Yaser Zarook
        This paper considers the problem of minimizing make-span and maximum tardiness simultaneously for scheduling jobs under non-identical job sizes, dynamic job arrivals, incompatible job families,and sequence-dependentfamily setup time on the single batch- processor, where More
        This paper considers the problem of minimizing make-span and maximum tardiness simultaneously for scheduling jobs under non-identical job sizes, dynamic job arrivals, incompatible job families,and sequence-dependentfamily setup time on the single batch- processor, where split size of jobs is allowed between batches. At first, a new Mixed Integer Linear Programming (MILP) model is proposed for this problem; then, it is solved by -constraint method.Since this problem is NP-hard, a bi-objective genetic algorithm (BOGA) is offered for real-sized problems. The efficiency of the proposed BOGA is evaluated to be comparedwith many test problemsby -constraint method based on performance measures. The results show that the proposed BOGAis found to be more efficient and faster than the -constraint method in generating Pareto fronts in most cases. Manuscript profile
      • Open Access Article

        4 - The Preemptive Just-in-time Scheduling Problem in a Flow Shop Scheduling System
        Javad Rezaeian Sadegh Hosseini-Kia Iraj Mahdavi
        Flow shop scheduling problem has a wide application in the manufacturing and has attracted much attention in academic fields. From other point, on time delivery of products and services is a major necessity of companies’ todays; early and tardy delivery times will More
        Flow shop scheduling problem has a wide application in the manufacturing and has attracted much attention in academic fields. From other point, on time delivery of products and services is a major necessity of companies’ todays; early and tardy delivery times will result additional cost such as holding or penalty costs. In this paper, just-in-time (JIT) flow shop scheduling problem with preemption and machine idle time assumptions is considered in which objective function is minimizing the sum of weighted earliness and tardiness. A new non-linear mathematical model is formulated for this problem and due to high complexity of the problem meta-heuristic approaches have been applied to solve the problem for finding optimal solution. The parameters of algorithms are set by Taguchi method. Each parameter is tested in three levels. By implementation of many problems with different sizes these levels are determined .The proposed model is solved by three meta-heuristic algorithms: genetic algorithm (GA), imperialist competitive algorithm (ICA) and hybrid of GA and ICA. To evaluate the performance of the proposed algorithms many test problems have been designed. The Computational results indicate the superiority of the performance of hybrid approach than GA and ICA in finding thebest solution in reasonable computational time. Manuscript profile
      • Open Access Article

        5 - Meta heuristic for Minimizing Makespan in a Flow-line Manufacturing Cell with Sequence Dependent Family Setup Times
        Behzad Nikjo Javad Rezaeian
        This paper presents a new mathematical model for the problem of scheduling part families and jobs within each part family in a flow line manufacturing cell where the setup times for each family are sequence dependent and it is desired to minimize the maximum completion More
        This paper presents a new mathematical model for the problem of scheduling part families and jobs within each part family in a flow line manufacturing cell where the setup times for each family are sequence dependent and it is desired to minimize the maximum completion time of the last job on the last machine (makespan) while processing parts (jobs) in each family together. Gaining an optimal solution for this type of complex problem in large sizes in reasonable computational time using traditional approaches or optimization tools is extremely difficult. A meta-heuristic method based on Simulated Annealing (SA) is proposed to solve the presented model. Based on the computational analyses, the proposed algorithm was found efficient and effective at finding good quality solutions. Manuscript profile
      • Open Access Article

        6 - Developing a Permutation Method Using Tabu Search Algorithm: A Case Study of Ranking Some Countries of West Asia and North Africa Based on Important Development Criteria
        Javad Rezaeian Keyvan Shokoufi Shahab Poursafary
        The recent years have witnessed an increasing attention to the methods of multiple attribute decision making in solving the problems of the real world due to their shorter time of calculation and easy application. One of these methods is the ‘permutation method&rs More
        The recent years have witnessed an increasing attention to the methods of multiple attribute decision making in solving the problems of the real world due to their shorter time of calculation and easy application. One of these methods is the ‘permutation method’ which has a strong logic in connection with ranking issues, but when the number of alternatives increases, solving problems through this method becomes NP-hard. So, meta-heuristic algorithm based on Tabu search is used to find optimum or near optimum solutions at a reasonable computational time for large size problems. This research is an attempt to apply the ‘permutation method’ to rank some countries of the West Asia and the North Africa based on the development criteria. Knowing the situation of each country as compared with other countries, particularly the respective neighbouring countries, is one of the most important standards for the assessment of performance and planning for the future activities. Manuscript profile