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Multi-objective optimization using genetic algorithms: A tutorial
Multi-objective formulations are realistic models for many complex engineering optimization
problems. In many real-life problems, objectives under consideration conflict with each …
problems. In many real-life problems, objectives under consideration conflict with each …
[PDF][PDF] Multi-objective particle swarm optimizers: A survey of the state-of-the-art
The success of the Particle Swarm Optimization (PSO) algorithm as a single-objective
optimizer (mainly when dealing with continuous search spaces) has motivated researchers …
optimizer (mainly when dealing with continuous search spaces) has motivated researchers …
Genetic algorithm based approach for autonomous mobile robot path planning
In this study, an improved crossover operator is suggested, for solving path planning
problems using genetic algorithms (GA) in static environment. GA has been widely applied …
problems using genetic algorithms (GA) in static environment. GA has been widely applied …
Multiobjective optimization problems with complicated Pareto sets, MOEA/D and NSGA-II
Partly due to lack of test problems, the impact of the Pareto set (PS) shapes on the
performance of evolutionary algorithms has not yet attracted much attention. This paper …
performance of evolutionary algorithms has not yet attracted much attention. This paper …
A multi-facet survey on memetic computation
Memetic computation is a paradigm that uses the notion of meme (s) as units of information
encoded in computational representations for the purpose of problem-solving. It covers a …
encoded in computational representations for the purpose of problem-solving. It covers a …
A competitive-cooperative coevolutionary paradigm for dynamic multiobjective optimization
In addition to the need for satisfying several competing objectives, many real-world
applications are also dynamic and require the optimization algorithm to track the changing …
applications are also dynamic and require the optimization algorithm to track the changing …
Balance between genetic search and local search in memetic algorithms for multiobjective permutation flowshop scheduling
This paper shows how the performance of evolutionary multiobjective optimization (EMO)
algorithms can be improved by hybridization with local search. The main positive effect of …
algorithms can be improved by hybridization with local search. The main positive effect of …
Multiobjective immune algorithm with nondominated neighbor-based selection
Abstract Nondominated Neighbor Immune Algorithm (NNIA) is proposed for multiobjective
optimization by using a novel nondominated neighbor-based selection technique, an …
optimization by using a novel nondominated neighbor-based selection technique, an …
Multi-objective vehicle routing problem with time windows using goal programming and genetic algorithm
This paper presents a new model and solution for multi-objective vehicle routing problem
with time windows (VRPTW) using goal programming and genetic algorithm that in which …
with time windows (VRPTW) using goal programming and genetic algorithm that in which …
A new multi-objective particle swarm optimization algorithm based on decomposition
C Dai, Y Wang, M Ye - Information Sciences, 2015 - Elsevier
The diversity of solutions is of great importance for multi-objective evolutionary algorithms. In
this paper, a new multi-objective particle swarm optimization algorithm based on …
this paper, a new multi-objective particle swarm optimization algorithm based on …