Using goal programming on estimated Pareto fronts to solve multiobjective problems

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.

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Modern 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.

Item Type: Conference or Workshop Item (Paper)
Schools/Departments: University of Nottingham, UK > Faculty of Science > School of Computer Science
Depositing User: Landa-Silva, Dario
Date Deposited: 08 Dec 2017 10:33
Last Modified: 04 May 2020 19:28

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