Multi-objective genetic local search algorithm

TLDR

The paper proposes a hybrid algorithm to identify all non-dominated solutions of a multi-objective optimization problem. The algorithm combines genetic operations with a local search applied to each individual, leaving final solution selection to the decision maker. Computer simulations on flowshop scheduling problems show the algorithm’s high search ability.

Abstract

Proposes a hybrid algorithm for finding a set of non-dominated solutions of a multi-objective optimization problem. In the proposed algorithm, a local search procedure is applied to each solution (i.e. to each individual) generated by genetic operations. The aim of the proposed algorithm is not to determine a single final solution but to try to find all the non-dominated solutions of a multi-objective optimization problem. The choice of the final solution is left to the decision maker's preference. The high searching ability of the proposed algorithm is demonstrated by computer simulations on flowshop scheduling problems.