Parallel machine scheduling with batch deliveries to minimize total flow time and delivery cost |
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| Authors: | Hua Gong Lixin Tang Joseph Y.T. Leung |
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| Affiliation: | 1. College of Science, Shenyang Ligong University, Shenyang, China;2. Institute of Industrial Engineering & Logistics Optimization, Northeastern University, Shenyang, China;3. Department of Computer Science, New Jersey Institute of Technology, Newark, New Jersey |
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| Abstract: | Motivated by the flow of products in the iron and steel industry, we study an identical and parallel machine scheduling problem with batch deliveries, where jobs finished on the parallel machines are delivered to customers in batches. Each delivery batch has a capacity and incurs a cost. The objective is to find a coordinated production and delivery schedule that minimizes the total flow time of jobs plus the total delivery cost. This problem is an extension of the problem considered by Hall and Potts, Ann Oper Res 135 (2005) 41–64, who studied a two‐machine problem with an unbounded number of transporters and unbounded delivery capacity. We first provide a dynamic programming algorithm to solve a special case with a given job assignment to the machines. A heuristic algorithm is then presented for the general problem, and its worst‐case performance ratio is analyzed. The computational results show that the heuristic algorithm can generate near‐optimal solutions. Finally, we offer a fully polynomial‐time approximation scheme for a fixed number of machines. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 492–502, 2016 |
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| Keywords: | parallel machines batch delivery FPTAS worst‐case performance dynamic programming |
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