LAUSR

ABSTRACT The conventional assignment problem is unable to handle scenarios that may arise due to different working modes of machines leading to multiple cost and time entries corresponding to a job–machine pair. The present article deals with this problem and models it as a multi-choice bi-objective assignment problem, the two objectives being assignment cost and bottleneck time. Two different solution procedures are presented based on the Decision-Maker's (DM's) preference structure. First, when the DM provides his/her preference structure as goals, a solution methodology is proposed using goal programming and its different multi-choice variants. In the second case, when no preference is provided by the DM, a two-step approach is presented that iteratively solves a multi-choice cost-minimizing assignment problem to obtain all Pareto-optimal time–cost pairs and finally, based on the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS), a single efficient pair is obtained. The algorithm is successfully implemented using the CPLEX optimization package and tested on various test problems.