Using goal programming on estimated Pareto fronts to solve multiobjective problemsTools Pinheiro, Rodrigo Lankaites, Landa-Silva, Dario, Laesanklang, Wasakorn and Constantino, Ademir Aparecido (2018) Using goal programming on estimated Pareto fronts to solve multiobjective problems. In: 7th International Conference on Operations Research and Enterprise Systems (ICORES 2018), 24-26 January 2018, Funchal, Portugal. Full text not available from this repository.AbstractModern multiobjective algorithms can be computationally inefficient in producing good approximation sets for highly constrained many-objective problems. Such problems are common in real-world applications where decision-makers need to assess multiple conflicting objectives. Also, different instances of real-world problems often share similar fitness landscapes because key parts of the data are the same across these instances. We we propose a novel methodology that consists of solving one instance of a given problem scenario using computationally expensive multiobjective algorithms to obtain a good approximation set and then using Goal Programming with efficient single-objective algorithms to solve other instances of the same problem scenario. We propose three goal-based objective functions and show that on a real-world home healthcare planning problem the methodology can produce improved results in a shorter computation time.
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