We consider the bicriteria scheduling problem of minimizing the number of tardy jobs and average flowtime on a single machine. This problem, which is known to be NP-hard, is important in practice, as the former criterion conveys the customer's position, and the latter reflects the manufacturer's perspective in the supply chain. We propose four new heuristics to solve this multiobjective scheduling problem. Two of these heuristics are constructive algorithms based on beam search methodology. The other two are metaheuristic approaches using a genetic algorithm and tabu-search. Our computational experiments indicate that the proposed beam search heuristics find efficient schedules optimally in most cases and perform better than the existing heuristics in the literature.
Recently, focusing on the minimization of both flowtime and number of tardy jobs, Erenay et al. propose an algorithm based on a beam-search methodology and observe that it provides efficient schedules in most cases, comparing to other metaheuristic approaches REF .
New solution methods for single machine bicriteria scheduling problem: Minimization of average flowtime and number of tardy jobs
Eur. J. Oper. Res.
Eur. J. Oper. Res.
Computer Science Mathematics