O P E N I N V E N T O R Y R O U T I N G P R O B L E M C O N S I D E R I N G F U E L R E D U C T I O N, S O L V I N G M E T H O D: D I F F E R E N T I A L E V O L U T I O N A L G O R I T H M
Author(s):
Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
Global warming is one of the biggest challenges of industries and organizations. Greenhouse gas emissions are the main cause of global warming. One of the major sources of GHG emissions is transportation equipment. In addition, it plays a major role in the production of these gases due to logistics and transportation activities. Since inventory routing problem solves the vehicle routing problem and inventory levels simultaneously, it has a significant role in reducing costs. So to obtain a model to minimize the cost of fuel for this problem is important. Furthermore, in many distribution companies, vehicles are rented, and there is no need to return to the depot after discharge. In cases where companies do not own a vehicle fleet, or their private fleet is in satisfactory for fully satisfying customer demand, distribution services (or at least a part of them) are either entrusted to external contractors, or assigned to a hired vehicle fleet. In these cases, vehicles are not required to return to the central depot after their deliveries have been satisfied. The above- described distribution model is referred to as the Open Vehicle Routing Problem (OVRP). Therefore, the goal of the OVRP is to design a set of Hamiltonian paths (open routes) to satisfy customer demand. In this paper, a model is provided for inventory routing problem by considering the reduction of fuel consumption and reduction of the costs of inventory, driver and using vehicles in a limited planning horizon. To solve this problem, a combined improved metaheuristic method, based on Differential evolutionary algorithm and constructive Clarke and Wright algorithm, is presented. To validate the proposed solution, in the small size, the proposed algorithm was compared with the exact solution for several problem instances. In the large size, the proposed algorithm was compared with the base algorithm. The result confirms the good performance of the proposed algorithm.
Keywords:
Language:
Persian
Published:
Industrial Engineering & Management Sharif, Volume:33 Issue: 2, 2018
Pages:
15 to 25
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