Genetic algorithms for supply-chain scheduling: A case study in the distribution of ready-mixed concrete |
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Authors: | David Naso Michele Surico Biagio Turchiano Uzay Kaymak |
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Affiliation: | 1. Politecnico di Bari, Dipartimento di Elettrotecnica ed Elettronica, Via Re David, 200, 70125 Bari, Italy;2. Erasmus University Rotterdam, Faculty of Economics, Department of Computer Science, P.O. Box 1738, 3000 DR, Rotterdam, The Netherlands |
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Abstract: | The coordination of just-in-time production and transportation in a network of partially independent facilities to guarantee timely delivery to distributed customers is one of the most challenging aspect of supply chain management. From a theoretical perspective, the timely production/distribution can be viewed as a hybrid combination of planning, scheduling and routing problems, each notoriously affected by nearly prohibitive combinatorial complexity. From a practical viewpoint, the problem calls for a trade-off between risks and profits. This paper focuses on the ready-mixed concrete delivery: in addition to the mentioned complexity, strict time-constraints forbid both earliness and lateness of the supply. After developing a detailed model of the considered problem, we propose a novel meta-heuristic approach based on a hybrid genetic algorithm combined with constructive heuristics. A detailed case study derived from industrial data is used to illustrate the potential of the proposed approach. |
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Keywords: | Genetic algorithms Scheduling Heuristics Supply chain management |
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