Local Search in Combinatorial Optimization

By Yves Crama, A. Kolen, Erwin Pesch. Artificial Neural Networks, 2018

1,453 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Industrial and Manufacturing Engineering

View Paper: https://www.semanticscholar.org/paper/bdbe833e1d5fc8dd04aceb3161def616b7fe77d4

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Citations in the corpus

The Theory and Practice of Simulated Annealing (2003, methodology): “Mühlenbein (1997) presents a theoretical analysis of genetic algorithms based on population genetics.”
Metaheuristic research: a comprehensive survey (2018, methodology): “Table 4 Acronyms of metaheuristics abbreviations used in this study Abbreviations Acronyms AAA Alienated Ant Algorithm (Uymaz et al. 2015) AAA2 Artificial Algae Algorithm (Bandieramonte et al. 2010) ABC Artificial Bee Colony (Karaboga 2005) ABO African Buffalo Optimization (Odili and Mohmad Kahar 20”
Optimizing OSPF/IS-IS weights in a changing world (2002, methodology): “Our technique for tuning a weight setting with as few weight changes as possible is a novel general adaptation of the classical local search approach of combinatorial optimization [1] , and we expect it to find many other applications in areas where parameter changes are undesirable.”
The Algorithm Design Manual (2020, methodology): “The different heuristic search techniques are ably presented in Aarts and Lenstra [AL97], which I strongly recommend for those interested in learning more about heuristic searches.”
Estimating maximum likelihood phylogenies with PhyML. (2009, background): “Note however that deterministic methods are generally faster than stochastic optimisation approaches and sufficient for numerous optimisation problems (48).”
Heuristics for cardinality constrained portfolio optimisation (2000, background): “…problem is minimise w i w j σ ij (8) subject to w i µ i = R * (9) w i = 1 (10) z i = K (11) ε i z i ≤ w i ≤ δ i z i i=1,...,N (12) z i ∈[0] [1] i=1,...,N (13) Equation (8) minimises the total variance (risk) associated with the portfolio whilst equation (9) ensures that the portfolio has…”
Designing Fast Absorbing Markov Chains (2014, methodology): “2012) and local search techniques for combinatorial search and optimization (Aarts and Lenstra 2003; Hoos and Stützle 2004).”
Internet traffic engineering by optimizing OSPF weights (2000, background): “An extensive survey of local search and its application can be found in Aarts and Lenstra [9].”
Simple Black-Box Adversarial Perturbations for Deep Networks (2016, methodology): “We utilize a local-search procedure, which is an incomplete search procedure that is widely used for solving combinatorial problems appearing in diverse domains such as graph clustering, scheduling, logistics, and verification [Lenstra, 1997].”
An Ant Colony System Hybridized with a New Local Search for the Sequential Ordering Problem (2000, background): “It consists of finding a minimum weight Hamiltonian path on a directed graph with weights on the arcs and the nodes, subject to precedence constraints among nodes.”
PAPR reduction of OFDM signals using a reduced complexity PTS technique (2004, methodology): “Here, we propose a novel PTS technique based on gradient descent search which is useful in solving combinatorial optimization problems [8].”