Recent work has shown the promise in using local-search “probes” as a basis for directing a backtracking-based refinement search. In this approach, the decision about the next refinement step is based on an interposed phase of sampling possible (but not necessarily feasible) variable assignments by local search. This information is then used to decide on which refinement to take, i.e., as a kin...

This papers aims at providing a combined strategy for solving systems of equalities and inequalities. The combined strategy uses two types of steps: a global search step and a local search step. The global step relies on a tabu search heuristic and the local step uses a deterministic search known as Hooke and Jeeves. The choice of step, at each iteration, is based on the level of reduction of t...

Forward-chaining heuristic search is a well-established and popular paradigm for planning. It is, however, characterised by two key weaknesses. First, search is guided by a domain-independent heuristic which although applicable in a wide range of domains, can often give poor guidance. Second, the metaheuristics used to control forward-chaining planning are often weak, using simple local-search ...

This paper investigates a hyper-heuristic algorithm for the permutation flow shop problem(FSP) to find a sequence to minimize the makespan. In comparison with existing approaches, our proposed hyper-heuristic algorithm based on multi-agent architecture includes two levels: low level heuristic agents(LLHAs) do local search in the solution domain and hyper-heuristic agent(HHA) manages low level h...

Dynamic features of the recently introduced extremal optimization heuristic are analyzed. Numerical studies of this evolutionary search heuristic show that it performs optimally at a transition between a jammed and an diffusive state. Using a simple, annealed model, some of the key features of extremal optimization are explained. In particular, it is verified that the dynamics of local search p...

One way to design a local search algorithm that is effective on many types of instances is allowing this algorithm to switch among heuristics. In this paper, we refer to the way in which non-weighting algorithm adaptGWSAT+ selects a variable to flip, as heuristic adaptGWSAT+, the way in which clause weighting algorithm RSAPS selects a variable to flip, as heuristic RSAPS, and the way in which v...

Using a simple, annealed model, some of the key features of the recently introduced extremal optimization heuristic are demonstrated. In particular, it is shown that the dynamics of local search possesses a generic critical point under the variation of its sole parameter, separating phases of too greedy (non-ergodic, jammed) and too random (ergodic) exploration. Comparison of various local sear...

In this paper, we investigate application of various options of algorithms with greedy agglomerative heuristic procedure for object clustering problems in continuous space in combination with various local search methods. We propose new modifications of the greedy agglomerative heuristic algorithms with local search in SWAP neighborhood for the p-medoid problems and j-means procedure for contin...

The transformation or derivation problem treated by most "problem-solving" programs is expressed in a formal notation, and various methods for "problem-solving" are reviewed. The conventio­ nal search tree is generalized into a search lattice which can accomodate multiple-input opera­ tors, e.g. resolution. The paper argues that descriptions of heuristic methods can be signi­ ficantly compacted...