Results 11 to 20 of about 34,025 (156)
Theory of Randomized Search Heuristics [PDF]
, 2011 Randomized search heuristics such as evolutionary algorithms, genetic algorithms, evolution strategies, ant colony and particle swarm optimization turn out to be highly successful for optimization in practice. The theory of randomized search heuristics, which has been growing rapidly in the last five years, also attempts to explain the success of the ...
Anne Auger, Benjamin Doerr
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Commercial Territory Design for a Distribution Firm with New Constructive and Destructive Heuristics [PDF]
International Journal of Computational Intelligence Systems, 2012 A commercial territory design problem with compactness maximization criterion subject to territory balancing and connectivity is addressed. Four new heuristics based on Greedy Randomized Adaptive Search Procedures within a location-allocation scheme for ...
Jaime Cano-Belmán +2 more
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On the use of biased-randomized algorithms for solving non-smooth optimization problems [PDF]
, 2020 Soft constraints are quite common in real-life applications. For example, in freight transportation, the fleet size can be enlarged by outsourcing part of the distribution service and some deliveries to customers can be postponed as well; in inventory ...
Ferrer Biosca, Albert +4 more
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Local search-based heuristics for the multiobjective multidimensional knapsack problem
Production, 2012 In real optimization problems it is generally desirable to optimize more than one performance criterion (or objective) at the same time. The goal of the multiobjective combinatorial optimization (MOCO) is to optimize simultaneously r > 1 objectives.
Dalessandro Soares Vianna +1 more
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BMC Health Services Research, 2023 Background Appointment non-attendance – often referred to as “missed appointments”, “patient no-show”, or “did not attend (DNA)” – causes volatility in health systems around the world. Of the different approaches that can be adopted to reduce patient non-
Kalin Werner +6 more
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Local search-based heuristics for the multiobjective multidimensional knapsack problem
Production, 2013 In real optimization problems it is generally desirable to optimize more than one performance criterion (or objective) at the same time. The goal of the multiobjective combinatorial optimization (MOCO) is to optimize simultaneously r > 1 objectives.
Dalessandro Soares Vianna +1 more
doaj +1 more source
Greedy Randomized Adaptive Search and Variable Neighbourhood Search for the minimum labelling spanning tree problem [PDF]
, 2009 This paper studies heuristics for the minimum labelling spanning tree (MLST) problem. The purpose is to find a spanning tree using edges that are as similar as possible.
Avis +28 more
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Theoretical Computer Science, 1999 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Efficient heuristic algorithms for the blocking flow shop scheduling problem with total flow time minimization [PDF]
, 2015 This paper proposes two constructive heuristics, i.e. HPF1 and HPF2, for the blocking flow shop problem in order to minimize the total flow time. They differ mainly in the criterion used to select the first job in the sequence since, as it is shown, its ...
Companys Pascual, Ramón +1 more
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Parameterized Complexity Analysis of Randomized Search Heuristics [PDF]
, 2019 This chapter compiles a number of results that apply the theory of parameterized algorithmics to the running-time analysis of randomized search heuristics such as evolutionary algorithms. The parameterized approach articulates the running time of algorithms solving combinatorial problems in finer detail than traditional approaches from classical ...
Neumann, F., Sutton, A.M.
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