8 research outputs found

    A Dynamic Heuristic for the Stochastic Unrelated Parallel Machine Scheduling Problem

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    This paper addresses the problem of batch scheduling in an unrelated parallel machine environment with sequence dependent setup times and an objective of minimizing the total weighted mean completion time. The jobs\u27 processing times and setup times are stochastic for better depiction of the real world. This is a NP-hard problem and in this paper, new heuristics are developed and compared to existing ones using simulation. The results and analysis obtained from the computational experiments proved the superiority of the proposed algorithm PMWP over the other algorithms presented

    ПОСТРОЕНИЕ РАСПИСАНИЙ ДЛЯ ОДНОСТАДИЙНЫХ СИСТЕМ ОБСЛУЖИВАНИЯ

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    Приведен обзор результатов, полученных в лаборатории математической кибернетики ОИПИ НАН наук Беларуси по решению задач теории расписаний для одностадийных детерминированных систем обслуживания

    Spatial Scheduling Algorithms for Production Planning Problems

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    Spatial resource allocation is an important consideration in shipbuilding and large-scale manufacturing industries. Spatial scheduling problems (SSP) involve the non-overlapping arrangement of jobs within a limited physical workspace such that some scheduling objective is optimized. Since jobs are heavy and occupy large areas, they cannot be moved once set up, requiring that the same contiguous units of space be assigned throughout the duration of their processing time. This adds an additional level of complexity to the general scheduling problem, due to which solving large instances of the problem becomes computationally intractable. The aim of this study is to gain a deeper understanding of the relationship between the spatial and temporal components of the problem. We exploit these acquired insights on problem characteristics to aid in devising solution procedures that perform well in practice. Much of the literature on SSP focuses on the objective of minimizing the makespan of the schedule. We concentrate our efforts towards the minimum sum of completion times objective and state several interesting results encountered in the pursuit of developing fast and reliable solution methods for this problem. Specifically, we develop mixed-integer programming models that identify groups of jobs (batches) that can be scheduled simultaneously. We identify scenarios where batching is useful and ones where batching jobs provides a solution with a worse objective function value. We present computational analysis on large instances and prove an approximation factor on the performance of this method, under certain conditions. We also provide greedy and list-scheduling heuristics for the problem and compare their objectives with the optimal solution. Based on the instances we tested for both batching and list-scheduling approaches, our assessment is that scheduling jobs similar in processing times within the same space yields good solutions. If processing times are sufficiently different, then grouping jobs together, although seemingly makes a more effective use of the space, does not necessarily result in a lower sum of completion times

    Integrated machine-scheduling and inventory planning of door manufacturing operations at OYAK Renault factory

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    Ankara : The Department of Industrial Engineering and the Graduate School of Engineering and Science of Bilkent University, 2012.Thesis (Master's) -- Bilkent University, 2012.Includes bibliographical references.A car passes through press, body shell, painting and assembly stages during its manufacturing process. Due to the increased competition among car manufacturers, they aim to continuously advance and improve their processes. In this study, we analyze planning operations for the production of front/back and left/right doors in body shell department of Bursa Oyak-Renault factory and propose heuristic algorithms to improve their planning processes. In this study, we present four different mathematical models and two heuristics approaches which decrease the current costs of the company particularly with respect to inventory carrying and setup perspectives. In the body shell department of the company, there are two parallel manufacturing cells which produces doors to be assembled on the consumption line. The effective planning and scheduling of the jobs on these lines requires solving the problem of integrated machine-scheduling and inventory planning subject to inclusive eligibility constraints and sequence independent setup times with job availability in flexible manufacturing cells of the body shell department. The novelty in the models lie in the integration of inventory planning and production scheduling decisions with the aim of streamlining operations of the door manufacturing cells with the consumption line. One of the proposed heuristic approaches is Rolling Horizon Algorithm (RHA) which divides the planning horizon into sub-intervals and solves the problem by rolling the solutions through sub-intervals. The other proposed algorithm is Two-Pass Algorithm which divides the planning horizon into sub-intervals and solves each sub-problem in each sub-interval to optimality for two times by maintaining the starting and ending inventory levels feasible. These approaches are implemented with Gurobi optimization software and Java programming language and applied within a decision support system that supports daily planning activities.Bozkaya, NurcanM.S
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