Genetic Algorithms in Supply Chain Scheduling of Ready-Mixed Concrete

David Naso, Michele Surico, Biagio Turchiano and Uzay Kaymak ()

ERIM Report Series Research in Management from Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam

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 aspects of supply chain management. From the theoretical perspective, the timely production/distribution can be viewed as a hybrid combination of planning, scheduling and routing problem, 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-made 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.

Keywords: concrete delivery; genetic algorithms; meta-heuristics; supply chain management (search for similar items in EconPapers)
JEL-codes: C61 M M11 R4 (search for similar items in EconPapers)
Date: 2004-11-12
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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