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Edward,â€œGuided Local Search
, 1995
"... Abstract Combinatorial explosion problem is a well known phenomenon that prevents complete algorithms from solving many reallife combinatorial optimization problems. In many situations, heuristic search methods are needed. This chapter describes the principles of Guided Local Search (GLS) and Fast ..."
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Cited by 56 (5 self)
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Abstract Combinatorial explosion problem is a well known phenomenon that prevents complete algorithms from solving many reallife combinatorial optimization problems. In many situations, heuristic search methods are needed. This chapter describes the principles of Guided Local Search (GLS) and Fast Local Search (FLS) and surveys their applications. GLS is a penaltybased metaheuristic algorithm that sits on top of other local search algorithms, with the aim to improve their efficiency and robustness. FLS is a way of reducing the size of the neighbourhood to improve the efficiency of local search. The chapter also provides guidance for implementing and using GLS and FLS. Four problems, representative of general application categories, are examined with detailed information provided on how to build a GLSbased method in each case.
Partial constraint satisfaction problems and guided local search
 Proc., Practical Application of Constraint Technology (PACT'96
, 1996
"... A largely unexplored aspect of Constraint Satisfaction Problem (CSP) is that of overconstrained instances for which no solution exists that satisfies all the constraints. In these problems, mentioned in the literature as Partial Constraint Satisfaction Problems (PCSPs), we are often looking for sol ..."
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Cited by 31 (12 self)
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A largely unexplored aspect of Constraint Satisfaction Problem (CSP) is that of overconstrained instances for which no solution exists that satisfies all the constraints. In these problems, mentioned in the literature as Partial Constraint Satisfaction Problems (PCSPs), we are often looking for solutions which violate the minimum number of constraints. In more realistic settings, constraints violations incur different costs and solutions are sought that minimize the total cost from constraint violations and possibly other criteria. Problems in this category present enormous difficulty to complete search algorithms. In practical terms, complete search has more or less to resemble the traditional Branch and Bound taking no advantage of the efficient pruning techniques recently developed for CSPs. In this report, we examine how the stochastic search method of Guided Local Search (GLS) can be applied to these problems. The effectiveness of the method is demonstrated on instances of the Radio Link Frequency Assignment Problem (RLFAP), which is a realworld Partial CSP.
Removing Node Overlapping in Graph Layout Using Constrained Optimization
, 2000
"... . Although graph drawing has been extensively studied, little attention has been paid to the problem of node overlapping. The problem arises because almost all existing graph layout algorithms assume that nodes are points. In practice, however, nodes may be labelled and these labels may overlap. We ..."
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Cited by 5 (0 self)
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. Although graph drawing has been extensively studied, little attention has been paid to the problem of node overlapping. The problem arises because almost all existing graph layout algorithms assume that nodes are points. In practice, however, nodes may be labelled and these labels may overlap. We propose four dierent approaches for removing node overlapping, all of which are based on constrained optimization techniques. The rst is the simplest. It performs the minimal linear scaling which will remove nodeoverlapping. The second approach relies on formulating the node overlapping problem as a convex quadratic programming problem which can then be solved by any quadratic solver. The disadvantage is that since constraints must be linear the node overlapping constraints cannot be expressed directly but must be strengthened to obtain a linear constraint strong enough to ensure no node overlapping. The third and fourth approaches are based on local search methods. The third is an adapta...
Constructing Driver Schedules using Iterative Repair
, 2000
"... The bus driver scheduling problem can be represented as a set partitioning or set covering problem. In this form, large instances can be tackled successfully by TRACS II, a system based on integer linear programming. However, the problem has key features that make it different from general set parti ..."
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Cited by 1 (1 self)
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The bus driver scheduling problem can be represented as a set partitioning or set covering problem. In this form, large instances can be tackled successfully by TRACS II, a system based on integer linear programming. However, the problem has key features that make it different from general set partitioning or set covering problems and it has been found to be hard for local search methods. For these reasons, examples of this problem have been submitted to CSPlib to use as benchmarks. Presented here is an investigation into using a local search technique, GENET, to tackle these driver scheduling problems. Although the solutions are not yet comparable with TRACS II, we believe our experience of applying GENET to this problem and making significant improvements over our initial simplistic model will be useful to other researchers wishing to use similar techniques for other problems. Further improvements to the GENET model are suggested.
GUIDED LOCAL SEARCH FOR QUERY REFORMULATION USING WEIGHT PROPAGATION
"... A new technique for query reformulation that assesses the relevance of retrieved documents using weight propagation is proposed. The technique uses a Guided Local Search (GLS) in conjunction with the latent semantic indexing model (to semantically cluster documents together) and Lexical Matching (LM ..."
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Cited by 1 (0 self)
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A new technique for query reformulation that assesses the relevance of retrieved documents using weight propagation is proposed. The technique uses a Guided Local Search (GLS) in conjunction with the latent semantic indexing model (to semantically cluster documents together) and Lexical Matching (LM). The GLS algorithm is used to construct a minimum spanning tree that is later employed in the reformulation process. The computations done for Singular Value Decomposition (SVD), LM and the minimum spanning tree are necessary overheads that occur only initially and all subsequent work is based on them. Our experimental results reveal the effectiveness of the new technique.