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Big bang–big crunch (BBBC) algorithm is a fairly novel gradient-free optimisation algorithm. It is based on theories of evolution of the universe, namely the big bang and big crunch theory. The big challenge in BBBC is that it is easily trapped in local optima. In this paper, chaotic-based strategies are incorporated into BBBC to tackle this challenge. Five(More)
Teaching–learning-based optimisation (TLBO) is an emerging gradient-free optimisation algorithm inspired by interactions between students and teacher in classrooms. TLBO has no control parameter to be tuned by user. This property makes it popular in research community. It has been successfully applied to challenging optimisation problems in different areas.(More)
Artificial immune system algorithm (AIS) is a population-based global heuristic optimisation algorithm. It is inspired by immune system of human bodies. Alleviating premature convergence problem of heuristic optimisation algorithms is a hot research area. In this study, chaotic-based strategies are embedded into AIS to alleviate its premature convergence(More)
Almost all real-world optimisation problems are constrained. Solving constrained problems is difficult for optimisation techniques. In this paper, different constraint handling strategies used in heuristic optimisation algorithms and especially particle swarm optimisation (PSO) are reviewed. Since PSO is a very common optimisation algorithm, this paper can(More)
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