Multi-objective meta-heuristics: An overview of the current state-of-the-art

By Dylan F. Jones, S. K. Mirrazavi, M. Tamiz. European Journal of Operational Research, 2002

592 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/e7853e55320cb703db57ef3d357d7ff3dbe4226a

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Citations in the corpus

Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions (2014, methodology): “, 2010), there has been a lack of uptake by decision makers (Jones et al., 2002; Oliveira and Loucks, 1997).”
Review of job shop scheduling research and its new perspectives under Industry 4.0 (2017, methodology): “Early generic meta-heuristic algorithms include genetic algorithm and Tabu search method (Jones et al. 2002).”
Multiobjective Optimization in Bioinformatics and Computational Biology (2007, unknown): “…is conducted with respect to a single problem (MOP) can be defined mathematically as: goal, but the possibility of optimizing multiple objectives simultaneously is rapidly becoming more recognized [3], [4], 00minimize00 z ¼fðxÞ¼ðf1ðxÞ;f2ðxÞ; ... ;fmðxÞÞ ð1Þ [5], [6], [7], [8], [9], [10], [11].”
A Survey of Multi-Objective Optimization in Wireless Sensor Networks: Metrics, Algorithms, and Open Problems (2016, background): “Over the most recent decade, metaheuristics have made substantial progress in approximate search methods for solving complex optimization problems [188].”
Multi-objective optimization using genetic algorithms: A tutorial (2006, background): “Jones et al. [ 25 ] reported that 90% of the approaches to multi-”
Ltd Registered in England and Wales Registered Number : 1072954 Registered office : (2004, methodology): “Meta-heuristics have become prominent approaches in tackling complex, multi-objective problems (Jones et al. 2002). Lin and Kwok (2006) applied meta-heuristics of a tabu search and simulated annealing on real data and simulated data, so as to compare their performances under both simultaneous and se”