Approximation of the Set of Efficient Objective Vectors for Large Scale MOLP
A new method which presents the overall structure of efficient criterion vectors (N hereafter) for large scale MOLP is introduced. The proposed algorithm ASEOV (Approximation of the Set of Efficient Objective Vectors) insures full coverage of N, with corresponding coverage precision indicated. The DM can guide the determination procedure by assessing the coverage allowance on each criterion. Combined with proper interactive methods, this insight over N obtained through ASEOV can help a DM in assessing his preference and reduce his burden in deriving the final best compromise solution. An illustrative example is presented.
KeywordsExtreme Point None None Supporting Hyperplane Representative Subset Criterion Vector
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