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.

Additional Metadata
Keywords genetic algorithms, heuristics, scheduling, supply chain management
JEL Optimization Techniques; Programming Models; Dynamic Analysis (jel C61), Business Administration and Business Economics; Marketing; Accounting (jel M), Production Management (jel M11), Transportation Systems (jel R4)
Persistent URL,
Series ERIM Top-Core Articles , Econometric Institute Reprint Series
Journal European Journal of Operational Research
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