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Metaheuristics for solving mathematical programming problems

Vitor Washiya, Aurélio de Oliveira

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Abstract

This undergraduate research aims to study metaheuristics for solving mathematical programming problems. In optimization's context, metaheuristics are strategies which use problem specific knowledge to, stochastically use solutions worse than the current in order to avoid local maximum or minimum. The literature about metaheuristics is huge and continues in expansion, mostly by its commercial interest, once most real problems are far too large to be solved by exact algorithms. This project considered a wide variety of metaheuristics and focused on a particular one: The Ant Colony Optmization applied to the Symmetric Travelling Salesman Problem (TSP).

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What this paper is about

This undergraduate research aims to study metaheuristics for solving mathematical programming problems. In optimization's context, metaheuristics are strategies which use problem specific knowledge to, stochastically use solutions worse than the current in order to avoid local maximum or minimum. The literature about metaheuristics is huge and continues in expansion, mostly by its commercial interest, once most real problems are far too large to be solved by exact algorithms. This project considered a wide variety of metaheuristics and focused on a particular one: The Ant Colony Optmization applied to the Symmetric Travelling Salesman Problem (TSP).

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Available abstract

This undergraduate research aims to study metaheuristics for solving mathematical programming problems. In optimization's context, metaheuristics are strategies which use problem specific knowledge to, stochastically use solutions worse than the current in order to avoid local maximum or minimum. The literature about metaheuristics is huge and continues in expansion, mostly by its commercial interest, once most real problems are far too large to be solved by exact algorithms. This project considered a wide variety of metaheuristics and focused on a particular one: The Ant Colony Optmization applied to the Symmetric Travelling Salesman Problem (TSP).

Key concepts: Metaheuristic, Parallel metaheuristic, Mathematical optimization, Ant colony optimization algorithms, Travelling salesman problem, Computer science, Context (archaeology), Variety (cybernetics)

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