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Research Report on Automatic Synthesis of Local Search Neighborhood Operators

Mateusz Ślażyński
2019 Electronic Proceedings in Theoretical Computer Science  
Constraint Programming (CP) and Local Search (LS) are different paradigms for dealing with combinatorial search and optimization problems.  ...  We consider a limited formal language that we call a Neighborhood Definition Language, used to specify the neighborhood operators in a fine-grained and declarative manner.  ...  It supports several search strategies, including LS, and allows the definition of the neighborhood in a declarative manner as a composition of basic moves.  ... 
doi:10.4204/eptcs.306.59 fatcat:c6iatvjdvbasjdqoney33rqqhi

Enhancing Differential Evolution Utilizing Proximity-Based Mutation Operators

Michael G. Epitropakis, Dimitris K. Tasoulis, Nicos G. Pavlidis, Vassilis P. Plagianakos, Michael N. Vrahatis
2011 IEEE Transactions on Evolutionary Computation  
The proposed framework can be applied to any mutation strategy with minimal changes.  ...  Motivated by the different manner in which various search operators behave, we propose a novel framework based on the proximity characteristics among the individual solutions as they evolve.  ...  , e.g., Hooke Jeeves algorithm, a stochastic local search, and simulated annealing.  ... 
doi:10.1109/tevc.2010.2083670 fatcat:k2z2j5grn5cgllinmanbbzxhsm

Metaheuristics in combinatorial optimization

Christian Blum, Andrea Roli
2003 ACM Computing Surveys  
Neighborhood Search & Scatter Search • Guided Local Search & Fast Local Search • Cellular Automata & Artificial Immune Systems • Oral Presentations & Competition Grading • Project: 50% • Final  ...  . • FLS -Fast Local Search -A way of reducing the size of the neighborhood so as to improve the efficiency of LS.  ... 
doi:10.1145/937503.937505 fatcat:nvqxwlqkyjfvvavs55z5xroomm

Scenario-based Modeling Approach and Scatter Search Algorithm for the Stochastic Slab Allocation Problem in Steel Industry

Yana Lv, Gongshu Wang, Lixin Tang
2014 ISIJ International  
Moreover, we introduce a random perturbation strategy to avoid search process being tapped in local optimum.  ...  Thus, a scatter search algorithm with directed local search based on follow-up technique is proposed to solve the problem approximately.  ...  Solution Improvement Method We adopt the local search method based on follow-up technique and a speedup strategy. The key of local search is constructing the neighborhood.  ... 
doi:10.2355/isijinternational.54.1324 fatcat:o6jdcmgcaneyhgslmj4vit4agi

Simulation optimization using metamodels

Russell R. Barton
2009 Proceedings of the 2009 Winter Simulation Conference (WSC)  
Many iterative optimization methods are designed to be used in conjunction with deterministic objective functions.  ...  This tutorial surveys both local and global metamodel-based optimization methods.  ...  For local fitting strategies, the fitting and optimization steps alternate: as the optimization search moves, new local regions of θ space are explored, and new metamodel approximations are fitted.  ... 
doi:10.1109/wsc.2009.5429328 dblp:conf/wsc/Barton09 fatcat:frnjtoonjnfchdp5l3wowsrlsi

Gnowee: A Hybrid Metaheuristic Optimization Algorithm for Constrained, Black Box, Combinatorial Mixed-Integer Design [article]

James Bevins, Rachel Slaybaugh
2018 arXiv   pre-print
developed to optimize complex nuclear design problems; the motivating research problem was the design of material stack-ups to modify neutron energy spectra to specific targeted spectra for applications in  ...  Gnowee's hybrid metaheuristic framework is a new combination of a set of diverse, robust heuristics that appropriately balance diversification and intensification strategies across a wide range of optimization  ...  SA heavily relies on the directional search, neighborhood search, and hill climbing heuristics, resulting in rapid convergence to a local optimum.  ... 
arXiv:1804.05429v1 fatcat:qk6qbjkquzfbhhprsxtkv32al4

Comprehensive learning particle swarm optimizer for global optimization of multimodal functions

J.J. Liang, A.K. Qin, P.N. Suganthan, S. Baskar
2006 IEEE Transactions on Evolutionary Computation  
The results demonstrate good performance of the CLPSO in solving multimodal problems when compared with eight other recent variants of the PSO.  ...  This strategy enables the diversity of the swarm to be preserved to discourage premature convergence.  ...  In [17] , Hu and Eberhart also used a dynamic neighborhood where closest particles in the performance space are selected to be its new neighborhood in each generation.  ... 
doi:10.1109/tevc.2005.857610 fatcat:z25iygonz5be5ms423b2okrfrq

Collaborative Strategy for Grey Wolf Optimization Algorithm

Esra F. Alzaghoul, Sandi N. Fakhouri
2018 Modern Applied Science  
In this paper, we proposed a novel optimization algorithm called collaborative strategy for grey wolf optimizer (CSGWO).  ...  This algorithm enhances the behaviour of GWO that enhances the search feature to search for more points in the search space, whereas more groups will search for the global minimal points.  ...  In fact, stagnation in local solutions can be resolved by promoting exploration. local optima avoidance of CSGWO is also competitive as seen in the results of the hybrid Composite test functions that provide  ... 
doi:10.5539/mas.v12n7p73 fatcat:vhut5uui2jd6nogf226aqxvlpe

A comparative study of particle swarm optimization and its variants for phase stability and equilibrium calculations in multicomponent reactive and non-reactive systems

Adrián Bonilla-Petriciolet, Juan Gabriel Segovia-Hernández
2010 Fluid Phase Equilibria  
Particle swarm optimization is a novel evolutionary stochastic global optimization method that has gained popularity in the chemical engineering community.  ...  This optimization strategy has been successfully used for several applications including thermodynamic calculations.  ...  Local search methods with and without decoupling strategies are frequently used to solve these equations in conjunction with mass balance restrictions.  ... 
doi:10.1016/j.fluid.2009.11.008 fatcat:e3x3unedufav7cjy2wgilyo4fu

Modified Local Search Heuristics for the Symmetric Traveling Salesman Problem

A. Blažinskas, A. Lenkevičius
2013 Information Technology and Control  
We are also examining the performance of these extensions being used in an iterated local search (ILS) paradigm.  ...  In this paper, we investigate some modified local search (LS) heuristics for the solution of symmetric traveling salesman problem (TSP).  ...  The introduced strategies for extending the neighborhoods and integrating the descending local search and stochastic perturbations seem to be of rather general character, so they may be applicable for  ... 
doi:10.5755/j01.itc.42.3.1301 fatcat:el6ilffer5gq7fbei6epold644

A Guaranteed Global Convergence Social Cognitive Optimizer

Jia-ze Sun, Shu-yan Wang, Hao Chen
2014 Mathematical Problems in Engineering  
The global convergence of the improved SCO algorithm is guaranteed by the strategy of periodic restart in use under the conditions of participating in comparison, which helps to avoid the premature convergence  ...  From the analysis of the traditional social cognitive optimization (SCO) in theory, we see that traditional SCO is not guaranteed to converge to the global optimization solution with probability one.  ...  agents, on behalf of human individuals, in possession of a knowledge point in the knowledge library, act observational learning via the neighborhood local searching by observing the selected model from  ... 
doi:10.1155/2014/534162 fatcat:chmh45nvm5adri5iafwhf3eyiu

Optimal Stochastic Process Optimizer: A New Metaheuristic Algorithm with Adaptive Exploration-Exploitation Property

Jiahong Xu, Lihong Xu
2021 IEEE Access  
those regions of a search space within the neighborhood of previously visited points."  ...  The receding sampling strategy helps OSPO to avoid falling into local optima.  ... 
doi:10.1109/access.2021.3101939 fatcat:rjfbtwa3qbdtvecggnedlyzgeu

Applying Multi-Moves in Parallel Genetic Algorithm for the Flow Shop Problem

W. Bozejko, M. Wodecki, Theodore E. Simos, George Maroulis
2007 AIP Conference Proceedings  
The matter of using multi-moves in parallel genetic algorithms is discussed in the paper Computational experiments are done for the flow shop, the classic NP-hard problem of the combinatorial optimization  ...  Because of a NP-hardness of determining the optimal multi-swap, an heuristic method of the neighborhood searching is apphed. It consists in stochastic sampling of the neighborhood space.  ...  Practical approaches to solve such problems are local search algorithms based on the neighborhood's search.  ... 
doi:10.1063/1.2835952 fatcat:owss52ffsvfpdccblbpugfn2tm

LFA: A Lévy Walk and Firefly-Based Search Algorithm: Application to Multi-Target Search and Multi-Robot Foraging

Ouarda Zedadra, Antonio Guerrieri, Hamid Seridi
2022 Big Data and Cognitive Computing  
It is beneficial when targets are sparsely distributed in the search space.  ...  In this paper, we propose a swarm intelligence-based search algorithm called Lévy walk and Firefly-based Algorithm (LFA), which is a hybridization of the two aforementioned algorithms.  ...  Robots use six elementary states: Global search (in the composite state Global exploration), Local search (in the composite state Local exploration), Follow robot light (in the composite state Following  ... 
doi:10.3390/bdcc6010022 fatcat:5vbvtxbbgfgl3igumaprtz3fmi

Why Local Search Excels in Expression Simplification [article]

Ben Ruijl, Aske Plaat, Jos Vermaseren, Jaap van den Herik
2014 arXiv   pre-print
As a result, the Horner space is appropriate to be explored by Stochastic Local Search (SLS), which has only two parameters: the number of iterations (computation time) and the neighborhood structure.  ...  In this work, we investigate the state space properties of Horner schemes and find that the domain is relatively flat and contains only a few local minima.  ...  ACKNOWLEDGMENTS This work is supported in part by the ERC Advanced Grant no. 320651, "HEPGAME".  ... 
arXiv:1409.5223v1 fatcat:shogso2jjzbgdlcflyoiy7dodu
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