Abstract
This paper deals with the NP-hard single-machine total weighted tardiness problem with sequence dependent setup times. Incorporating fuzzy sets and genetic operators, a novel ant colony optimization algorithm is developed for the problem. In the proposed algorithm, artificial ants construct solutions as orders of jobs based on the heuristic information as well as pheromone trails. To calculate the heuristic information, three well-known priority rules are adopted as fuzzy sets and then aggregated. When all artificial ants have terminated their constructions, genetic operators such as crossover and mutation are applied to generate new regions of the solution space. A local search is then performed to improve the performance quality of some of the solutions found. Moreover, at run-time the pheromone trails are locally as well as globally updated, and limited between lower and upper bounds. The proposed algorithm is experimented on a set of benchmark problems from the literature and compared with other metah...
Highlights
Scheduling problems have been considered for over five decades
The pheromone trails are reset if no improvement can be made for 30 successive iterations, and the algorithm terminates when either the total number of iterations reaches 150 or no improvement can be made for 50 successive iterations
A novel ant colony algorithm is developed for the single-machine total weighted tardiness scheduling problem with sequence dependent setup times
Summary
Scheduling problems have been considered for over five decades. In this context, some research efforts are concerned with due date related objectives such as the maximum/total tardiness, the total weighted tardiness and the number of tardy jobs. The total weighted tardiness as the performance criterion has attracted a large amount of literature on scheduling. Many researchers have studied the single-machine total weighted tardiness scheduling problem — denoted as 1//∑wjTj by the three-field notation — and examined with different approaches. The single-machine total weighted tardiness scheduling problem with sequence dependent setup times (STWTSDS) — denoted in the literature as 1/sij/∑wjTj — is strongly NP-hard too, because the STWTSDS is clearly more complicated than the problem with sequence independent setup times
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