Future paths for integer programming and links to artificial intelligence
Computers and Operations Research - Special issue: Applications of integer programming
The general employee scheduling problem: an integration of MS and AI
Computers and Operations Research - Special issue: Applications of integer programming
Combinatorial optimization: algorithms and complexity
Combinatorial optimization: algorithms and complexity
Global optimization and simulated annealing
Mathematical Programming: Series A and B
Computers and Operations Research
A parallel adaptive tabu search approach
Parallel Computing
Experiments with new stochastic global optimization search techniques
Computers and Operations Research
Neutrality in fitness landscapes
Applied Mathematics and Computation
Local Search in Combinatorial Optimization
Local Search in Combinatorial Optimization
Tabu Search
Guided Local Search — an Illustrative Example in Function Optimisation
BT Technology Journal
Fitness Distance Correlation and Ridge Functions
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
The Density of States - A Measure of the Difficulty of Optimisation Problems
PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
A Racing Algorithm for Configuring Metaheuristics
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Local Optimization and the Traveling Salesman Problem
ICALP '90 Proceedings of the 17th International Colloquium on Automata, Languages and Programming
MALLBA: A Library of Skeletons for Combinatorial Optimisation (Research Note)
Euro-Par '02 Proceedings of the 8th International Euro-Par Conference on Parallel Processing
Evolving Objects: A General Purpose Evolutionary Computation Library
Selected Papers from the 5th European Conference on Artificial Evolution
Localizer++: An Open Library for local Search
Localizer++: An Open Library for local Search
EasyLocal++: an object-oriented framework for the flexible design of local-search algorithms
Software—Practice & Experience
Stochastic Local Search: Foundations & Applications
Stochastic Local Search: Foundations & Applications
Representations for Genetic and Evolutionary Algorithms
Representations for Genetic and Evolutionary Algorithms
Fine-Tuning of Algorithms Using Fractional Experimental Designs and Local Search
Operations Research
An effective two-stage simulated annealing algorithm for the minimum linear arrangement problem
Computers and Operations Research
A study of NK landscapes' basins and local optima networks
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Parallel and distributed local search in COMET
Computers and Operations Research
Fitness landscapes and graphs: multimodularity, ruggedness and neutrality
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
Relevance estimation and value calibration of evolutionary algorithm parameters
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Metaheuristics: From Design to Implementation
Metaheuristics: From Design to Implementation
ParamILS: an automatic algorithm configuration framework
Journal of Artificial Intelligence Research
PISA: a platform and programming language independent interface for search algorithms
EMO'03 Proceedings of the 2nd international conference on Evolutionary multi-criterion optimization
SLS'07 Proceedings of the 2007 international conference on Engineering stochastic local search algorithms: designing, implementing and analyzing effective heuristics
An integrated white+black box approach for designing and tuning stochastic local search
CP'07 Proceedings of the 13th international conference on Principles and practice of constraint programming
First-improvement vs. best-improvement local optima networks of NK landscapes
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part I
Exploiting grid computation for solving the Vehicle Routing Problem
AICCSA '10 Proceedings of the ACS/IEEE International Conference on Computer Systems and Applications - AICCSA 2010
Metaheuristics based de novo protein sequencing: A new approach
Applied Soft Computing
Opt4J: a modular framework for meta-heuristic optimization
Proceedings of the 13th annual conference on Genetic and evolutionary computation
NILS: a neutrality-based iterated local search and its application to flowshop scheduling
EvoCOP'11 Proceedings of the 11th European conference on Evolutionary computation in combinatorial optimization
Towards paradisEO-MO-GPU: a framework for GPU-based local search metaheuristics
IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part I
Communications of the ACM
The min-conflict packing problem
Computers and Operations Research
Metaheuristic optimization frameworks: a survey and benchmarking
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special Issue on Bio-inspired Computing for Hybrid Information Technology
Software review: the ECJ toolkit
Genetic Programming and Evolvable Machines
On the neutrality of flowshop scheduling fitness landscapes
LION'05 Proceedings of the 5th international conference on Learning and Intelligent Optimization
The noising method: a new method for combinatorial optimization
Operations Research Letters
A probabilistic heuristic for a computationally difficult set covering problem
Operations Research Letters
Semi-greedy heuristics: An empirical study
Operations Research Letters
A hybrid metaheuristic for multiobjective unconstrained binary quadratic programming
Applied Soft Computing
| Hi-index | 0.00 |
This paper presents a general-purpose software framework dedicated to the design, the analysis and the implementation of local search metaheuristics: ParadisEO-MO. A substantial number of single solution-based local search metaheuristics has been proposed so far, and an attempt of unifying existing approaches is here presented. Based on a fine-grained decomposition, a conceptual model is proposed and is validated by regarding a number of state-of-the-art methodologies as simple variants of the same structure. This model is then incorporated into the ParadisEO-MO software framework. This framework has proven its efficiency and high flexibility by enabling the resolution of many academic and real-world optimization problems from science and industry.