Optimizing a bi-objective inventory model of a three-echelon supply chain using a tuned hybrid bat algorithm |
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Affiliation: | 1. Department of Chemical Engineering, Aristotle University of Thessaloniki, University Campus, Thessaloniki, 54124, Greece;2. Department of Applied Informatics, School of Information Sciences, University of Macedonia, 156 Egnatia Str., Thessaloniki 54636, Greece |
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Abstract: | This paper presents a bi-objective VMI problem in a single manufacturer-single vendor multi-retailer (SM-SV-MR) supply chain, which a redundancy allocation problem is incorporated. In the hybridized problem, a manufacturer produces a single item using several machines that work in series, and stores it in a warehouse to replenish one vendor who delivers it to several retailers using the shortest possible route. A novel meta-heuristic, called hybrid bat algorithm (HBA), with calibrated parameters is utilized to find a near-optimum solution. To show the efficiency of HBA, the results are compared to the ones using the traditional BA and a genetic algorithm. |
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Keywords: | Vendor managed inventory (VMI) Transportation cost Redundancy allocation problem (RAP) Hybrid bat algorithm Parameter tuning |
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