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        1 - A Hierarchical Production Planning and Finite Scheduling Framework for Part Families in Flexible Job-shop (with a case study)
        Davod Abachi fariborz jolai hasan haleh
        Tendency to optimization in last decades has resulted in creating multi-product manufacturing systems. Production planning in such systems is difficult, because optimal production volume that is calculated must be consistent with limitation of production system. Hence, More
        Tendency to optimization in last decades has resulted in creating multi-product manufacturing systems. Production planning in such systems is difficult, because optimal production volume that is calculated must be consistent with limitation of production system. Hence, integration has been proposed to decide about these problems concurrently. Main problem in integration is how we can relate production planning in medium-term timeframe with scheduling in short-term timeframe. Our contribution creates production planning and scheduling framework in flexible job shop environment with respect to time-limit of each machine in order to produce different parts families in automotive industry. Production planning and scheduling have iterative relationship. In this strategy information flow is transformed reciprocative between production planning and scheduling for satisfying time-limit of each machine. The proposed production planning has heuristic approach and renders a procedure to determine production priority of different part families based on safety stock. Scheduling is performed with ant colony optimization and assigns machine in order of priority to different part families on each frozen horizon. Results showed that, the proposed heuristic algorithm for planning decreased parts inventory at the end of planning horizon. Also, results of proposed ant colony optimization was near the optimal solution .The framework was performed to produce sixty four different part families in flexible job-shop with fourteen different machines. Output from this approach determined volume of production batches for part families on each frozen horizon and assigned different operations to machines. Manuscript profile
      • Open Access Article

        2 - Location-Allocation and Scheduling of Inbound and Outbound Trucks in Multiple Cross-Dockings Considering Breakdown Trucks
        javad Behnamian Seyed Mohammad Taghi Fatemi Ghomi Fariborz Jolai Pooya Heidary
        This paper studies multiple cross-dockings where the loads are transferred from origins (suppliers) to destinations (customers) through cross-docking facilities. Products are no longer stored in intermediate depots and incoming shipments are consolidated based on custom More
        This paper studies multiple cross-dockings where the loads are transferred from origins (suppliers) to destinations (customers) through cross-docking facilities. Products are no longer stored in intermediate depots and incoming shipments are consolidated based on customer demands and immediately delivered to them to their destinations. In this paper, each cross-docking has a covering radius that customers can be served by at least one cross-docking provided. In addition, this paper considers the breakdown of trucks. We present a two-stage model for the location of cross-docking centers and scheduling inbound and outbound trucks in multiple cross-dockings.We work on minimizing the transportation cost in a network by loading trucks in the supplier locations and route them to the customers via cross-docking facilities. The objective, in the first stage, is to minimize transportation cost of delivering products from suppliers to open cross-docks and cross-docks to the customers; in the second-stage, the objective is to minimize the makespans of open cross-dockings and the total weighted summation of completion time. Due to the difficulty of obtaining the optimum solution tomedium- and large-scale problems, we ‌propose four types of metaheuristic algorithms, i.e., genetic, simulated annealing, differential evolution, and hybrid algorithms.The result showed that simulated annealing is the best algorithm between the four algorithms. Manuscript profile