The production and delivery of rapidly perishable goods in distributed supply networks involves a number of tightly coupled decision and optimisation problems regarding the just-in-time production scheduling and the routing of the delivery vehicles in order to satisfy strict customer specified time-windows. Besides dealing with the typical combinatorial complexity related to activity assignment and synchronisation, effective methods must also provide robust schedules, coping with the stochastic perturbations (typically transportation delays) affecting the distribution process. In this paper, we propose a novel bi-objective meta-heuristic approach for robust scheduling. The proposed algorithm returns a set of solutions with different cost and risk tradeoffs, allowing the analyst to adapt the planning depending on the attitude to risk. The effectiveness of the approach is demonstrated by a real-world case concerning the production and distribution of ready-mixed concrete.

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Keywords Bismuth plating, Chlorine compounds, Combinatorial complexity, Concrete mixers, Delivery vehicles, Evolutionary approaches, Fuzzy logic, Fuzzy systems, Heuristic methods, Heuristic programming, International conferences, Metaheuristic approaches, Optimisation, Perishable goods, Production engineering, Ready-mixed concretes, Real-world, Risk trade offs, Robust scheduling, Scheduling, Stochastic perturbations, Supply networks, Synchronisation, Tightly coupled, Transportation delays
Persistent URL dx.doi.org/10.1109/FUZZY.2007.4295611, hdl.handle.net/1765/15992
Citation
Surico, M, Kaymak, U, Naso, D, & Dekker, R. (2007). A bi-objective evolutionary approach to robust scheduling. IEEE International Conference on Fuzzy Systems. doi:10.1109/FUZZY.2007.4295611