Learn 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)
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)
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)
In this paper, we present a novel discrepancy-based search technique implemented as an instance of the generic search procedures framework introduced in [10]. Our empirical results indicate that the Discrepancy-Bounded Depth First Search (DBDFS) procedure exhibits a number of good properties. As a discrepancy based search technique, it is able to quickly(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)
Coordination of the participants in the supply chain of a manufacturing enterprise is a key to agile reaction to unexpected events. As a starting point, we take a mediated approach to coordination: a single agent is responsible for recovery of the supply chain from a disruptive event. This mediator gathers commitment information from other agents and forms(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)
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)