Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Inver-over Operator for the TSP
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
A new representation and operators for genetic algorithms applied to grouping problems
Evolutionary Computation
Evolutionary algorithms for constrained parameter optimization problems
Evolutionary Computation
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The economic lot and delivery scheduling problem (ELDSP) involves a supply chain consisting of a supplier and an assembly facility, where direct shipments are made from one to the other. The supplier produces multiple components on a single machine or a production line. The assembly facility uses these components at a constant rate. The supplier incurs a sequence-independent setup cost and setup time each time the production line is changed over from one component to another. On the other hand, setup costs and times for the assembly facility are negligible. There is also a fixed charge for each delivery. The problem is to find a “just-in-time” schedule in which one production run of each component and a subsequent delivery of these components to the assembly facility occur in each cycle. The objective is to find the best sequence and cycle duration that minimizes the average cost per unit time of transportation, inventory at both the supplier and the assembly facility, and setup costs at the supplier. In this paper we investigate the usefulness of an evolutionary algorithm for solving this economic lot and delivery scheduling problem.