Multiobjective problem modeling of the capacitated vehicle routing problem with urgency in a pandemic period
Yükleniyor...
Dosyalar
Tarih
2023
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer London Ltd
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
This research is based on the capacitated vehicle routing problem with urgency where each vertex corresponds to a medical facility with a urgency level and the traveling vehicle could be contaminated. This contamination is defined as the infectiousness rate, which is defined for each vertex and each vehicle. At each visited vertex, this rate for the vehicle will be increased. Therefore time-total distance it is desired to react to vertex as fast as possible- and infectiousness rate are main issues in the problem. This problem is solved with multiobjective optimization algorithms in this research. As a multiobjective problem, two objectives are defined for this model: the time and the infectiousness, and will be solved using multiobjective optimization algorithms which are nondominated sorting genetic algorithm (NSGAII), grid-based evolutionary algorithm GrEA, hypervolume estimation algorithm HypE, strength Pareto evolutionary algorithm shift-based density estimation SPEA2-SDE, and reference points-based evolutionary algorithm.
Açıklama
Anahtar Kelimeler
Vehicle Routing Problem, Multiobjective Optimization Algorithm, Many Objective Optimization Algorithm, Optimization, Genetic Algorithm, Optimization
Kaynak
Neural Computing & Applications
WoS Q Değeri
Q2
Scopus Q Değeri
Q1
Cilt
35
Sayı
5
Künye
Altinoz, M., & Altinoz, O. T. (2023). Multiobjective problem modeling of the capacitated vehicle routing problem with urgency in a pandemic period. Neural Computing and Applications, 35(5), 3865-3882.
