Solving the bi-objective corridor allocation problem using a permutation-based genetic algorithm
The corridor allocation problem (CAP) seeks an effective placement of given facilities in two parallel rows on opposite sides of a central corridor. The placement of the facilities in both the rows starts from the same level along the corridor and no gap is allowed between two facilities of a row. The CAP is formulated here as a nonlinear bi-objective optimization problem, in which both the overall flow cost among the facilities and the length of the corridor are to be minimized. A permutation-based genetic algorithm (pGA) is applied to handle the CAP as an unconstrained bi-objective optimization problem. The performance of the pGA is demonstrated through its application to a number of instances of varying sizes available in the literature. The results presented in this paper can be used as benchmark instances in the future work on the CAP.
corridor allocation genetic algorithm combinatorial optimization multi-objective optimization