Multi-objective optimization of a real-world manufacturing process using cuckoo search

Abstract

This chapter describes the application of Cuckoo Search in simulation-based optimization of a real-world manufacturing process. The optimization problem is a combinatorial problem of setting 56 unique decision variables in a way that maximizes utilization of machines and at the same time minimizes tied-up capital. As in most real-world problems, the two optimization objectives are conflicting and improving performance on one of them deteriorates performance of the other. To handle the conflicting objectives, the original Cuckoo Search algorithm is extended based on the concepts of multi-objective Pareto-optimization. © 2014 Springer International Publishing Switzerland.