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Recent scheduling work has challenged the need for sophisticated heuristics such as those based on texture measurements. This paper examines these claims in the light of advances in scheduling technology. We compare a number of current heu-ristic commitment techniques against a texture-based heuris-tic. Our results demonstrate that texture-based heuristics(More)
Most classical scheduling formulations assume a fixed and known duration for each activity. In this paper, we weaken this assumption, requiring instead that each duration can be represented by an independent random variable with a known mean and variance. The best solutions are ones which have a high probability of achieving a good makespan. We first create(More)
Considerable effort has been spent extending the scope of planning beyond propositional domains to include, for example , time and numbers. Each extension has been designed as a separate specific semantic enrichment of the underlying planning model, with its own syntax and customised integration into a planning algorithm. Inspired by work on SAT Modulo(More)
We address the problem of computing a policy for fully observable non-deterministic (FOND) planning problems. By focusing on the relevant aspects of the state of the world, we introduce a series of improvements to the previous state of the art and extend the applicability of our planner, PRP, to work in an online setting. The use of state relevance allows(More)
Tabu search algorithms are among the most effective approaches for solving the job-shop scheduling problem (JSP). Yet, we have little understanding of why these algorithms work so well, and under what conditions. We develop a model of problem difficulty for tabu search in the JSP, borrowing from similar models developed for SAT and other NP-complete(More)
In this paper, we expand the scope of constraint-directed scheduling techniques to deal with the case where the scheduling problem includes alternative activities. That is, not only does the scheduling problem consist of determining when an activity is to execute, but also determining which set of alternative activities is to execute at all. Such problems(More)
While the exploitation of problem structure by heuristic search techniques has a long history in AI (Simon, 1973), many of the advances in constraint-directed scheduling technology in the 1990s have resulted from the creation of powerful propagation techniques. In this paper, we return to the hypothesis that understanding of problem structure plays a(More)
This paper addresses the question of allocating computational resources among a set of algorithms in order to achieve the best performance on a scheduling problem instance. Our primary motivation in addressing this problem is to reduce the expertise needed to apply constraint technology. Therefore, we investigate algorithm control techniques that make(More)
Despite a number of similarities, vehicle routing problems and scheduling problems are typically solved with different techniques. In this paper, we undertake a systematic study of problem characteristics that differ between vehicle routing and scheduling problems in order to identify those that are important for the performance of typical vehicle routing(More)