Pruning-Based Pareto Front Generation for Mixed-Discrete Bi-Objective Optimization

2013/06/07 by Seungbum Hong, SeungBum Hong, Hong, SeungBum +5
Computer Science · Decision Sciences · Mathematics · #Advanced Multi-Objective Optimization Algorithms #FOS: Mathematics #Metaheuristic Optimization Algorithms Research #Optimization and Control (math.OC) #Probabilistic and Robust Engineering Design #math.OC

paper · pdf · doi:10.48550/arxiv.1306.1589

4 pages, 3 figures, submitted to Structural and Multidisciplinary Optimization

arxiv created 2013/06/07 · openalex publication_date 2013/06/07 · arxiv updated 2013/06/10 · openalex created_date 2019/06/27 · openalex updated_date 2026/07/28

Abstract

This note proposes an effective pruning-based Pareto front generation method in mixed-discrete bi-objective optimization. The mixed-discrete problem is decomposed into multiple continuous subproblems; two-phase pruning steps identify and prune out non-contributory subproblems to the Pareto front construction. The efficacy of the proposed method is demonstrated on two benchmark examples.

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