I. Mahdavi, A. Jazayeri, M. Jahromi, R. Jafari, and H. Iranmanesh Abstract—One of the most important problems in production planning of flexible manufacturing system (FMS) is machine tool selection and operation allocation problem that directly influences the production costs and times .In this paper minimizing machining cost, set-up cost and material handling cost as a multi-objective problem in flexible manufacturing systems environment are considered. We present a 0-1 integer linear programming model for the multi- objective machine tool selection and operation allocation problem and due to the large scale nature of the problem, solving the problem to obtain optimal solution in a reasonable time is infeasible, Pareto- ant colony optimization (P-ACO) approach for solving the multi- objective problem in reasonable time is developed. Experimental results indicate effectiveness of the proposed algorithm for solving the problem. Keywords—Flexible manufacturing system; Production planning; Machine tool selection; Operation allocation; Multi- objective optimization; Metaheuristic. I. INTRODUCTION LEXIBLE manufacturing system consist of some multi functional machines that are link together through material-handling system and the whole of the system control by a central computer. A FMSs have advantage of two well known production systems, flow line for mass production and job shop for mid variety production, that due to this advantage more attention to theses systems is reasonable. Flexibility of these systems proposes different machine tool combinations for performing each operation that results several routes for each part type between machines. Each routes has specific completion time and production cost. We should finding a set of appropriate routes for parts that lead to effective production cost with considering limitation of resources. Also finding appropriate routees for each part or assignment of operations to appropriate machine tool combination is one of the difficult tasks in these environments I. Mahdavi, Assistant Professor, is with Department of Industrial Engineering, Mazandaran University of Science and Technology, Babol, Iran (+9891-11131380, e-mail:irajarash@rediffmail.com). A. Jazayeri, Graduate Student, is with Department of Industrial Engineering, Mazandaran University of Science and Technology, Babol, Iran (phone: +9891-25440956; fax+9821-55387926, e- mail:seyed_ali_jazayeri@yahoo.com). M. Jahromi, Graduate Student, is with Department of Industrial Management, Islamic Azad University, Khomein Branch, Iran (phone: +9893- 54015954, e-mail: mhm_jahromi@yahoo.com) R. Jafari, Graduate Student, is with Department of Industrial Management, Islamic Azad University, Khomein Branch, Iran (phone: +9891-23092075) H. Iranmanesh, Assistant Professor, is with "University of Tehran" & "Institute for Trade Studies & Research", Tehran, Iran (corresponding author, phone: +9821-88021067, fax: +9821- 88013102, e-mail: hiranmanesh@ut.ac.ir). and directly effect production costs and times. Researchers have developed different approaches for this problem. [4] developed a 0-1 mixed integer programming model to machine tool selection and operation allocation and presented an ant colony optimization approach to operation assignment in FMS with assuming that each machine has specific available time and tools can not transfer between machines during the production phases [4]. [5] presented a heuristic approach for tool selection in FMS based on the life over size ratio of each tool that used part AGVs and tool AGVs. [7] developed an integrated model that performs operation sequence and tool selection simultaneously into the direction that minimizes tool waiting time when the tool is absent, decision point of tool selection is not after finishing an operation by a tool but after machining a part in their paper. [8] presented an approach to production planning of FMS that having four objective: minimizing total flow time, machine workload unbalance, greatest machine workload and total cost using an efficient multi-objective genetic algorithm that make use of Pareto dominance relationship to solve the problem [8]. [9] represented a modeling for loading problem in FMS as 0-1 mixed integer programming problem and with the output of the model generated a detailed operation schedule [9]. [10] extended modeling of loading problem of FMSs and using a hybrid tabu search and simulated annealing- based heuristic approach to solve the problem of minimization of system unbalance and maximization of throughput are considered. [11] presented a heuristic based on multi stage programming approach to solve problem of minimization of unbalance while satisfying the technological constrains such as availability of machining time and tool slots. Because of the large-scale nature of many problems and solving of them in reasonable time is infeasible. Researchers have developed effective metheuristics. Each metaheuristic algorithms use a specific mechanism to escape from local optima. [1] initially proposed ant colony optimization (ACO) that is inspired by the behavior of real ants, ACO is a parallel search over several constructive computational threads based on local problem data and on a dynamic memory structure containing information on quality of previously obtained results. ACO is a construction procedure, a constructive heuristic start from a null solution and add elements to build a good complete solution, and probabilistically build solutions. ACO Iteratively adding solution components to partial solution till represents many solutions. In ACO ants work concurrently and independently. [2] first developed pareto ant colony optimization for multi- objective combinatorial optimization and applied P-ACO approach to solve the multi- objective portfolio selection problem that this approach P-ACO Approach to Assignment Problem in FMSs F World Academy of Science, Engineering and Technology International Journal of Industrial and Manufacturing Engineering Vol:2, No:6, 2008 787 International Scholarly and Scientific Research & Innovation 2(6) 2008 scholar.waset.org/1307-6892/14341 International Science Index, Industrial and Manufacturing Engineering Vol:2, No:6, 2008 waset.org/Publication/14341