An Immunized Ant Colony System Algorithm to Solve Unequal Area Facility Layout Problems Using Flexible Bay Structure
The Facility Layout Problem (FLP) is a typical combinational optimization problem. In this research, clonal selection algorithm (CSA) and ant colony system (ACS) are combined and an immunized ant colony system algorithm (IACS) is proposed to solve unequal-area facility layout problems using a flexible bay structure (FBS) representation. Four operations of CSA, clone, mutation, memory cells, and suppressor cells, are introduced in the ACS to improve the solution quality of initial ant solutions and to increase differences among ant solutions, so search capability of the IACO is enhanced. Datasets of well-known benchmark problems are used to evaluate the effectiveness of this approach. Compared with preview researches, the IACS can obtain the close or better solutions for some benchmark problems.
KeywordsUnequal-area facility layout Ant colony optimization Clonal selection algorithm Flexible bay structure Constrained combinatorial optimization
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