EMO '01 Proceedings of the First International Conference on Evolutionary Multi-Criterion Optimization
Running time analysis of evolutionary algorithmson a simplified multiobjective knapsack problem
Natural Computing: an international journal
A simple but powerful multiobjective hybrid genetic algorithm
Design and application of hybrid intelligent systems
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Genetic algorithm for the personnel assignment problem with multiple objectives
Information Sciences: an International Journal
Implementation of Simple Multiobjective Memetic Algorithms and Its Application to Knapsack Problems
International Journal of Hybrid Intelligent Systems
Computers and Operations Research
Effects of the use of non-geometric binary crossover on evolutionary multiobjective optimization
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Proceedings of the 10th annual conference on Genetic and evolutionary computation
EMO '09 Proceedings of the 5th International Conference on Evolutionary Multi-Criterion Optimization
Computers and Operations Research
Speed-up techniques for solving large-scale biobjective TSP
Computers and Operations Research
Multiobjective optimization problems with complicated Pareto sets, MOEA/D and NSGA-II
IEEE Transactions on Evolutionary Computation
The performance of a new version of MOEA/D on CEC09 unconstrained MOP test instances
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Optimization of scalarizing functions through evolutionary multiobjective optimization
EMO'07 Proceedings of the 4th international conference on Evolutionary multi-criterion optimization
EMO'07 Proceedings of the 4th international conference on Evolutionary multi-criterion optimization
A multiobjective metaheuristic for a mean-risk static stochastic knapsack problem
Computational Optimization and Applications
Expensive multiobjective optimization by MOEA/D with Gaussian process model
IEEE Transactions on Evolutionary Computation
Simultaneous use of different scalarizing functions in MOEA/D
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Evolutionary symbolic discovery for bioinformatics, systems and synthetic biology
Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
How to choose solutions for local search in multiobjective combinatorial memetic algorithms
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part I
A novel smart multi-objective particle swarm optimisation using decomposition
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part II
Diversity improvement by non-geometric binary crossover in evolutionary multiobjective optimization
IEEE Transactions on Evolutionary Computation
Very large-scale neighborhood search for solving multiobjective combinatorial optimization problems
EMO'11 Proceedings of the 6th international conference on Evolutionary multi-criterion optimization
A hybrid evolutionary metaheuristics (HEMH) applied on 0/1 multiobjective knapsack problems
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Multiple objective optimisation applied to route planning
Proceedings of the 13th annual conference on Genetic and evolutionary computation
An adaptive evolutionary multi-objective approach based on simulated annealing
Evolutionary Computation
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
GISMOO: A new hybrid genetic/immune strategy for multiple-objective optimization
Computers and Operations Research
Multi-objective probability collectives
EvoApplicatons'10 Proceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part I
Recombination of similar parents in EMO algorithms
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
Effects of removing overlapping solutions on the performance of the NSGA-II algorithm
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
Comparison between lamarckian and baldwinian repair on multiobjective 0/1 knapsack problems
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
Proceedings of the 14th annual conference on Genetic and evolutionary computation
HEMH2: an improved hybrid evolutionary metaheuristics for 0/1 multiobjective knapsack problems
SEAL'12 Proceedings of the 9th international conference on Simulated Evolution and Learning
A hybrid evolutionary approach with search strategy adaptation for mutiobjective optimization
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Comprehensive Survey of the Hybrid Evolutionary Algorithms
International Journal of Applied Evolutionary Computation
Fault tolerant embedded systems design by multi-objective optimization
Expert Systems with Applications: An International Journal
Computers & Mathematics with Applications
General framework for localised multi-objective evolutionary algorithms
Information Sciences: an International Journal
Variable and large neighborhood search to solve the multiobjective set covering problem
Journal of Heuristics
| Hi-index | 0.00 |
Multiple-objective metaheuristics, e.g., multiple-objective evolutionary algorithms, constitute one of the most active fields of multiple-objective optimization. Since 1985, a significant number of different methods have been proposed. However, only few comparative studies of the methods were performed on large-scale problems. We continue two comparative experiments on the multiple-objective 0/1 knapsack problem reported in the literature. We compare the performance of two multiple-objective genetic local search (MOGLS) algorithms to the best performers in the previous experiments using the same test instances. The results of our experiment indicate that our MOGLS algorithm generates better approximations to the nondominated set in the same number of functions evaluations than the other algorithms