TY - JOUR AU - Ab Halim, Huda Zuhrah AU - Mohd Azliana, Nureffa Natasha AU - Baharom, Nuridawati AU - Fauzi, Nur Fatihah AU - Ahmad Bakhtiar, Nurizatul Syarfinas AU - Khairudin, Nur Izzati PY - 2021/10/01 Y2 - 2024/03/29 TI - Green Inventory Routing Problem using Hybrid Genetic Algorithm JF - Journal of Computing Research and Innovation JA - JCRINN VL - 6 IS - 4 SE - General Computing DO - 10.24191/jcrinn.v6i4.254 UR - https://jcrinn.com/index.php/jcrinn/article/view/254_huda_zuhrah_uitm SP - 10-20 AB - <p><em>Carbon dioxide (CO<sub>2</sub>) is known as one of the largest sources of global warming. One of the ways to curb CO<sub>2</sub> 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 CO<sub>2</sub> 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.</em></p> ER -