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.