2022/06/12 by Sajal Chakroborty, Chakroborty, Sajal
Computer Science · Decision Sciences · Engineering · Mathematics · #Active set method #Algorithm #Artificial intelligence #Computer science #FOS: Mathematics #Fuzzy logic #Fuzzy number #Fuzzy set #General Mathematics (math.GM) #Mathematical optimization #Mathematics #Metaheuristic Optimization Algorithms Research #Multi-Criteria Decision Making #Nonlinear programming #Optimization and Mathematical Programming #Parametric programming #Parametric statistics #Quadratic equation #Quadratic programming
paper · pdf · doi:10.48550/arxiv.2206.07524
openalex publication_date 2022/06/12 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/06
The theory of fuzzy mathematics has been proven very effective for defining and solving optimization problems. Fuzzy quadratic programming (FQP) is a consequence of this approach. In this paper, an algorithm has been proposed to solve FQP with coefficients as triangular fuzzy numbers (TFN). The proposed algorithm converts FQP into two parametric quadratic programming (QP) problems. These QP solutions provide a lower and upper bound on the objective function of FQP. When these two values coincide, an optimal solution is achieved. This algorithm has been analyzed using a numerical example and compared with existing methods.