Open AccessGreen Inventory Routing Problem using Hybrid Genetic Algorithm
Author(s) -
Huda Zuhrah Ab Halim,
Nureffa Natasha Mohd Azliana,
Nuridawati Baharom,
Nur Fatihah Fauzi,
Nurizatul Syarfinas Ahmad Bakhtiar,
Norhazlin Khairudin
Publication year - 2021
Publication title -
journal of computing research and innovation
Language(s) - English
Resource type - Journals
ISSN - 2600-8793
DOI - 10.24191/jcrinn.v6i4.254
Subject(s) - fuel efficiency , supply chain , greenhouse gas , genetic algorithm , routing (electronic design automation) , total cost , computer science , mathematical optimization , operations research , supply chain network , consumption (sociology) , integer programming , environmental science , supply chain management , engineering , business , algorithm , mathematics , economics , automotive engineering , computer network , microeconomics , ecology , social science , marketing , sociology , biology
Carbon dioxide (CO2) is known as one of the largest sources of global warming. One of the ways to curb CO2 emissions is by considering the environmental aspect in the supply chain management. This paper analyses the influence of carbon emissions on the Inventory Routing Problem (IRP). The IRP network consists of a depot, an assembly plant and multiple suppliers. The deterministic demands vary and are determined by the assembly plant. Fixed transportation cost, fuel consumption cost and inventory holding cost are used to evaluate the system’s total cost in which fuel consumption cost is determined by fuel consumption rate, distance, and fuel price. Backordering and split pick-up are not allowed. The main purpose of this study is to analyze the distribution network especially the overall costs of the supply chain by considering the CO2 emissions as well. The problem is known as Green Inventory Routing Problem (GIRP). The mixed-integer linear programming of this problem is adopted from Cheng et al. wherein this study a different Hybrid Genetic Algorithm is proposed at mutation operator. As predicted, GIRP has a higher total cost as it considered fuel consumption cost together with the transportation and inventory costs. The results showed the algorithm led to different sequences of routings considering the carbon dioxide emission in the objective function.