Genetic algorithms for supply-chain scheduling: A case study in the distribution of ready-mixed concrete
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.
|Keywords||genetic algorithms, heuristics, scheduling, supply chain management|
|Persistent URL||dx.doi.org/10.1016/j.ejor.2005.12.019, hdl.handle.net/1765/19253|
Naso, D., Surico, M., Turchiano, B., & Kaymak, U.. (2007). Genetic algorithms for supply-chain scheduling: A case study in the distribution of ready-mixed concrete. European Journal of Operational Research, 177(3), 2069–2099. doi:10.1016/j.ejor.2005.12.019