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Novel Pareto-based meta-heuristics for solving multi-objective multi-item capacitated lot-sizing problems

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Abstract

Capacitated production lot-sizing problems (LSPs) are challenging problems to solve due to their combinatorial nature. We consider a multi-item capacitated LSP with setup times, safety stocks, and demand shortages plus lost sales and backorder considerations for various production methods (i.e., job shop, batch flow, or continuous flow among others). We use multi-objective mathematical programming to solve this problem with three conflicting objectives including: (i) minimizing the total production costs; (ii) leveling the production volume in different production periods; and (iii) producing a solution which is as close as possible to the just-in-time level. We also consider lost sales, backorders, safety stocks, storage space limitation, and capacity constraints. We propose two novel Pareto-based multi-objective meta-heuristic algorithms: multi-objective vibration damping optimization (MOVDO) and a multi-objective harmony search algorithm (MOHSA). We compare MOVDO and MOHSA with two well-known evolutionary algorithms called the non-dominated sorting genetic algorithm (NSGA-II) and multi-objective simulated annealing (MOSA) to demonstrate the efficiency and effectiveness of the proposed methods.

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Authors and Affiliations

  1. Young Researchers and Elite Club, Qazvin Branch, Islamic Azad University, Qazvin, Iran

    Vahid Hajipour

  2. Industrial Engineering Department, Bu-Ali Sina University, Hamedan, Iran

    AmirSaman Kheirkhah

  3. Business Systems and Analytics Department, Lindback Distinguished Chair of Information Systems and Decision Sciences, La Salle University, Philadelphia, PA, 19141, USA

    Madjid Tavana

  4. Business Information Systems Department, Faculty of Business Administration and Economics, University of Paderborn, 33098, Paderborn, Germany

    Madjid Tavana

  5. Department of Manufacturing Sciences and Logistics, Ecole des Mines de Saint-Etienne, 13541, Gardanne, France

    Nabil Absi

Authors
  1. Vahid Hajipour
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  2. AmirSaman Kheirkhah
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  3. Madjid Tavana
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  4. Nabil Absi
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Correspondence to Madjid Tavana.

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Hajipour, V., Kheirkhah, A., Tavana, M. et al. Novel Pareto-based meta-heuristics for solving multi-objective multi-item capacitated lot-sizing problems. Int J Adv Manuf Technol 80, 31–45 (2015). https://doi.org/10.1007/s00170-015-6993-6

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