The discussion provide a comprehensive overview of meta-heuristics, which are problem-solving techniques used to find good solutions for difficult optimisation problems. The discussion covers a wide range of meta-heuristic approaches, including genetic algorithms, simulated annealing, tabu search, variable neighbourhood search, and ant colony optimisation. We discuss the theory behind these methods, their practical implementation, and their application to real-world problems such as the traveling salesman problem, vehicle routing, and cutting and packing.The Entire Behavioural Science Reading List

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