Adaptive binary artificial bee colony for multi-dimensional knapsack problem
Küçük Resim Yok
Tarih
2021
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Gazi Univ, Fac Engineering Architecture
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
The efficiency and effectiveness of metaheuristic optimization algorithms is managed with diverse search and fast approximation in the solution space. A balanced exploration and exploitation capability is required to achieve by the neighborhood operators towards the aimed efficiency. The majority of metaheuristic algorithms use either single operator or limited to genetic operators, which impose serious boundaries upon performance. In order to avoid this limitation, multiple neighborhood operators can be used within the search process orchestrated by a selection scheme. In this study, an adaptive operator selection scheme is studied with multiple binary operators embedded within artificial bee colony algorithm to solve the multidimensional knapsack problem (MKP) as a renown NP-Hard combinatorial problem. It is implemented for modelling and solving many real-world problems, while it is not trivial to offer a good solution within a reasonable timeframe. A parametric study has been conducted for the approach proposed in this study. The success of the proposed approach has been demonstrated and discussed with comparative analysis using three different classes of benchmark problem sets.
Açıklama
Anahtar Kelimeler
Multi-dimensional knapsack problem, artificial bee colony, binary abc, adaptive abc
Kaynak
Journal of the Faculty of Engineering and Architecture of Gazi University
WoS Q Değeri
Q4
Scopus Q Değeri
Q2
Cilt
36
Sayı
4
