Multi-objective genetic algorithm and its applications to flowshop scheduling
Computers and Industrial Engineering
A computationally efficient evolutionary algorithm for real-parameter optimization
Evolutionary Computation
A population-based algorithm-generator for real-parameter optimization
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Approximating the Nondominated Front Using the Pareto Archived Evolution Strategy
Evolutionary Computation
Comparison of Multiobjective Evolutionary Algorithms: Empirical Results
Evolutionary Computation
A genetic algorithms based multi-objective neural net applied to noisy blast furnace data
Applied Soft Computing
A real-coded predator-prey genetic algorithm for multiobjective optimization
EMO'03 Proceedings of the 2nd international conference on Evolutionary multi-criterion optimization
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
Circle detection using electro-magnetism optimization
Information Sciences: an International Journal
Model fusion using fuzzy aggregation: Special applications to metal properties
Applied Soft Computing
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In this paper, a salient search and optimisation algorithm based on a new reduced space searching strategy, is presented. This algorithm originates from an idea which relates to a simple experience when humans search for an optimal solution to a 'real-life' problem, i.e. when humans search for a candidate solution given a certain objective, a large area tends to be scanned first; should one succeed in finding clues in relation to the predefined objective, then the search space is greatly reduced for a more detailed search. Furthermore, this new algorithm is extended to the multi-objective optimisation case. Simulation results of optimising some challenging benchmark problems suggest that both the proposed single-objective and multi-objective optimisation algorithms outperform some of the other well-known Evolutionary Algorithms (EAs). The proposed algorithms are further applied successfully to the optimal design problem of alloy steels, which aims at determining the optimal heat treatment regime and the required weight percentages for chemical composites to obtain the desired mechanical properties of steel hence minimising production costs and achieving the overarching aim of 'right-first-time production' of metals.