Minimizing the earliness and tardiness cost of a sequence of tasks on a single machine

Chrétienne, Philippe

RAIRO - Operations Research - Recherche Opérationnelle, Tome 35 (2001) no. 2, pp. 165-187.

Supposons que $n$ tâches doivent être exécutées par une machine dans un ordre fixé a priori. On connaît pour chaque tâche sa durée, la date souhaitée de son exécution et les coûts unitaires associés d’avance et de retard. On cherche à allouer à chaque tâche une date d’exécution de sorte que le coût total des avances et des retards soit minimum. Un algorithme de complexité $O(nlogn)$ a été proposé par Garey et al. pour le cas particulier de coûts unitaires. Nous proposons d’abord un algorithme de complexité $O(n^{2}logn)$ qui étend l’algorithme Garey et al. au cas de coûts asymétriques indépendants des tâches. Pour le cas général de coûts asymétriques dépendants des tâches, nous proposons un algorithme de complexité $O(n^{3}logn)$ fondé sur une propriété de dominance permettant de ramener le problème à la recherche d’un chemin de coût minimum dans un graphe valué sans circuit.

Assume that $n$ tasks must be processed by one machine in a fixed sequence. The processing time, the preferred starting time and the earliness and tardiness costs per time unit are known for each task. The problem is to allocate each task a starting time such that the total cost incurred by the early and tardy tasks is minimum. Garey et al. have proposed a nice $O(nlogn)$ algorithm for the special case of symmetric and task-independent costs. In this paper we first extend that algorithm to the case of asymmetric and task-independent cost without increasing its worst-case complexity. For the general case of asymmetric and task-dependent costs, we propose an $O(n^{3}logn)$ algorithm based on a strong dominance property that yields to model the scheduling problem as a minimum cost path in a valued directed acyclic graph.

Mots clés : scheduling, algorithm, complexity

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