Robust Operating Room Scheduling: A Two Stage Advanced Ant System

In this paper, we address the multiobjective surgical case scheduling (MOSCS) problem in a multioperating theatre environment with uncertain service times in order to minimise the makespan, the number of the nonscheduled surgical cases, robustness, stability, and nervousness.The planning contains two stages; in the first stage, the elective patients are scheduled considering two former criteria using a Pareto ant system and then in the second stage, after arriving emergency patients online, the plan is rescheduled considering three later objectives addition to makespan using a new max-min ant system.On the other hand, we take into account fuzzy numbers for processing times of all stages, and hereafter the problem called multiobjective fuzzy SCS.This problem is strongly an NP-hard optimisation problem; hence we employ a two-stage algorithm including a fuzzy Pareto envelope-based selection ant system so as to tackle the first stage of problem and a new multiobjective Max-Min ant system for solving the second stage of the problem.Moreover, this proposed approach is illustrated by providing three test cases.Therefore, the performance of the proposed algorithm on all test instances is compared to a basic multiobjective ant system under the fuzzy condition, namely Pareto strength ant colony optimisation.Consequently, computational experiments state that our proposed approach outperforms another algorithm, and the results indicate the efficiency and effectiveness of the proposed algorithm in comparison with the traditional algorithm for solving the problem.