New adaptive weight formulations for time-cost optimization
Yükleniyor...
Dosyalar
Tarih
2020
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Elsevier
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Modified Adaptive Weight Approach (MAWA) is one of the simplest methods used for solving time-cost opti-mization problems. This type of optimization problem, categorized as multi-objective optimization, can be solved with metaheuristic algorithms. Here, metaheuristic algorithms evaluate a randomly generated solution set, referred to as population, within the boundary condition of a solution space. The weight factor values determined by MAWA are applied to all solutions in the population without distinguishing the solutions in that population. However, the potential solutions in the population indicate different fitness properties concerning solution space. In this paper to solve time-cost optimization problems, new adaptive weight formulations are proposed. In contrast to MAWA, the novelty of this study’s formulations is to adaptively detect the weight factor value, depending on the solution‘s fitness in the population. The results obtained from the numerical experiments examined in this study show that the proposed formulations can improve the performance of MAWA and can find identical or slightly different Pareto results for investigated multi-objective optimization problems.
Açıklama
Anahtar Kelimeler
Multi-objective optimization, Weight approach, Modified adaptive weight approach, Time-cost optimization, Genetic algorithms
Kaynak
Structures
WoS Q Değeri
Q2
Scopus Q Değeri
Q1
Cilt
28
Sayı
Künye
Toğan, V., Berberoğlu, N., & Başağa, H. B. (2020). New adaptive weight formulations for time-cost optimization. Structures. 28, 2291-2299.
