Purpose: Intermittent demand appears sporadically, with some time periods not even displaying any demand at all. Even so, such patterns constitute considerable proportions of the total stock in many industrial settings. Forecasting intermittent demand is a rather difficult task but of critical importance for corresponding cost savings. The current study examines the empirical outcomes of three ...

There is a growing interest towards self configuring/tuning automated general-purpose reusable heuristic approaches for combinatorial optimisation, such as, hyper-heuristics. Hyper-heuristics are search methodologies which explore the space of heuristics rather than the solutions to solve a broad range of hard computational problems without requiring any expert intervention. There are two commo...

One of the annual issues that has to be addressed in English football is producing a fixture schedule for the holiday periods that reduces the travel distance for the fans and players. This problem can be seen as a minimisation problem which must abide to the constraints set by the Football Association. In this study, the performance of selection hyper-heuristics is investigated as a solution m...

The problem of scheduling a set of applications on a multiprocessor system has been investigated in a number of diierent points of view. This paper describes our work on the scheduling problem at the user level, where we have to distribute evenly the parallel tasks that compose a program among a set of processors. We investigated dynamic scheduling heuristics applied to loops on distributed-mem...

This paper deals with methods exploiting treedecomposition approaches for solving constraint networks. We consider here the practical efficiency of these approaches, by defining three classes of variable orders more and more dynamic which preserve the time complexity bound and an extension of this theoretical time complexity bound to increase the dynamic aspect of these orders. We propose heuri...

Controlled tabular adjustment is an SDL methodology based on a mixed integer linear programming model. We develop new hybrid heuristics and new metaheuristic learning approaches for solving this model, and examine their performance. Our new approaches are based on partitioning the problem into its discrete and continuous components, and first creating a hybrid that reduces the number of binary ...

Non Euclidean TSP construction heuristics and especially asymmetric TSP construc tion heuristics have been neglected in the literature by comparison with the extensive e orts devoted to studying Euclidean TSP construction heuristics This state of a airs is at odds with the fact that asymmetric models are relevant to a wider range of applica tions and indeed are uniformly more general that symme...

This paper describes and compares several heuristic approaches for the car sequencing problem. We first study greedy heuristics, and show that dynamic ones clearly outperform their static counterparts. We then describe local search and ant colony optimization (ACO) approaches, that both integrate greedy heuristics, and experimentally compare them on benchmark instances. ACO yields the best solu...

Testing of concurrent software is difficult due to the nondeterminism present in scheduling of concurrent threads. Existing testing approaches tackle this problem either using a modified scheduler which allows to systematically explore possible scheduling alternatives or using random or heuristic noise injection which allows to observe different scheduling scenarios. In this paper, we experimen...

A hyperheuristic is a high level procedure which searches over a space of low level heuristics rather than directly over the space of problem solutions. The sequence of low level heuristics, applied in an order which is intelligently determined by the hyperheuristic, form a solution method for the problem. In this paper, we consider a hyperheuristicbased methodology where a large set of low lev...