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Expert systems with applications v.98, 2018년, pp.1 - 10   SCI SCIE
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Formulations and branch-and-cut algorithms for multi-product multi-vehicle production routing problems with startup cost

Qiu, Yuzhuo (Corresponding author at: Jiangsu Key Laboratory of Modern Logistics, School of Marketing and Logistics Management, Nanjing University of Finance and Economics, Nanjing 210023, China. ) ; Wang, Liang (Jiangsu Key Laboratory of Modern Logistics, School of Marketing and Logistics Management, Nanjing University of Finance and Economics, Nanjing 210023, China ) ; Xu, Xiaoling (Jiangsu Key Laboratory of Modern Logistics, School of Marketing and Logistics Management, Nanjing University of Finance and Economics, Nanjing 210023, China ) ; Fang, Xuanjing (Jiangsu Key Laboratory of Modern Logistics, School of Marketing and Logistics Management, Nanjing University of Finance and Economics, Nanjing 210023, China ) ; Pardalos, Panos M. (Department of Industrial and Systems Engineering, Faculty of Engineering, University of Florida, Gainesville 32611, United States ) ;
  • 초록  

    Abstract In multi-product multi-vehicle production routing problems (MMPRPs), it is necessary to accurately model the capacity utilization of multiple products to obtain feasible production plans. Thus, start-up variables are required to model the capacity consumed or cost incurred when a machine starts a production batch, or when a machine switches from one product to another. In this work, we present a mixed integer linear programming model of the MMPRP with the startup cost (MMPRPSC), which is an extension of the single-item multi-vehicle production routing problem. It also generalizes the multi-item multi-vehicle inventory routing problems by incorporating production decisions. This formulation is tightened with three families of valid inequalities in which the generalized ( l, S ) inequalities are used in these problem settings for the first time. Using the formulation and valid inequalities, we implement a branch-and-cut algorithm for the solution of the MMPRPSC. Computational experiments also confirm the effectiveness of the valid inequalities. The computational results of a case study show a 15% percent decrease in the total cost. Highlights MILP models for multi-product multi-vehicle production routing problems with startup. Branch-and-cut algorithm with relax-and-fix heuristic. Big-bucket versus small-bucket formulation. Comparison with multi-product multi-vehicle inventory routing problems. Case study for multi-product multi-vehicle production routing problems with startup.


  • 주제어

    Routing .   Production planning .   Branch-and-cut .   Generalized (l, S) inequalities.  

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