Multi-objective optimization using genetic algorithms: A tutorial

A Konak, DW Coit, AE Smith - Reliability engineering & system safety, 2006‏ - Elsevier
Multi-objective formulations are realistic models for many complex engineering optimization
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

M Reyes-Sierra, CAC Coello - International journal of …, 2006‏ - webspace.ulbsibiu.ro
The success of the Particle Swarm Optimization (PSO) algorithm as a single-objective
optimizer (mainly when dealing with continuous search spaces) has motivated researchers …

Genetic algorithm based approach for autonomous mobile robot path planning

C Lamini, S Benhlima, A Elbekri - Procedia Computer Science, 2018‏ - Elsevier
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 …

Multiobjective optimization problems with complicated Pareto sets, MOEA/D and NSGA-II

H Li, Q Zhang - IEEE transactions on evolutionary computation, 2008‏ - ieeexplore.ieee.org
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 …

A multi-facet survey on memetic computation

X Chen, YS Ong, MH Lim… - IEEE Transactions on …, 2011‏ - ieeexplore.ieee.org
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 …

A competitive-cooperative coevolutionary paradigm for dynamic multiobjective optimization

CK Goh, KC Tan - IEEE Transactions on Evolutionary …, 2008‏ - ieeexplore.ieee.org
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 …

Balance between genetic search and local search in memetic algorithms for multiobjective permutation flowshop scheduling

H Ishibuchi, T Yoshida, T Murata - IEEE transactions on …, 2003‏ - ieeexplore.ieee.org
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 …

Multiobjective immune algorithm with nondominated neighbor-based selection

M Gong, L Jiao, H Du, L Bo - Evolutionary computation, 2008‏ - direct.mit.edu
Abstract Nondominated Neighbor Immune Algorithm (NNIA) is proposed for multiobjective
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

K Ghoseiri, SF Ghannadpour - Applied Soft Computing, 2010‏ - Elsevier
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 …

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 …