Abstract: Modern multiobjective algorithms can be computationally inefficient in producing good approximation sets for highly constrained many-objective ...
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 ...
A novel methodology that consists of solving one instance of a given problem scenario using computationally expensive multiobjective algorithms to obtain a ...
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Modern multiobjective algorithms can be computationally inefficient in producing good approximation sets for highly constrained many-objective problems.
Using Goal Programming on Estimated Pareto Fronts to Solve Multiobjective Problems.In Proceedings of the 7th International Conference on Operations Research ...
It is also necessary to do re-optimization using goal programming to minimize the achievement deviation of the goal function and Pareto front as a model of ...
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Goal programming problems can be solved by either assigning weights to individual deviation parameters of the objective function or by defining priorities for ...
They found that the. BOGA result was more efficient and faster than the ε-constraint method in generating the Pareto front. Sabouni and Jolai (2010) ...
The new algorithm is specifically designed to handle sets of points and produce good approximations of the whole Pareto front.