An Integrated Multi-Echelon Supply Chain Network Design Considering Stochastic Demand: A Genetic Algorithm Based Solution

Abstract

The growing trend of natural resources consumption has caused irreparable losses to the environment. The scientists believe that if environmental degradation continues at its current pace, the prospect of human life will be shrouded in mystery. One of the most effective ways to deal with the environmental adverse effects is by implementing green supply chains. In this study a multilevel mathematical model including supply, production, distribution and customer levels has been presented for routing-location-inventory in green supply chain. Vehicle routing between distribution centres and customers has been considered in the model. Establishment place of distribution centres among potential places is determined by the model. The distributors use continuous review policy (r, Q) to control the inventory. The proposed model object is to find an optimal supply chain with minimum costs. To validate the proposed model and measure its compliance with real world problems, GAMS IDE/ Cplex has been used. In order to measure the efficiency of the proposed model in large scale problems, a genetic algorithm has been used. The results confirm the efficiency of the proposed model as a practical tool for decision makers to solve location-inventory-routing problems in green supply chain. The proposed GA could reduce the solving time by 85% while reaching on the average 97% of optimal solution compared with exact method.

Oportunidades para la transformación digital de la cadena de suministro del sector bananero basado en software con inteligencia artificial

“…Por último, y no menos importante se presentan aportes de los AG en el área de almacenamiento y gestión de inventarios [45][46][47][48][49][50][51] y en el área de selección, evaluación de proveedores respecto a una demanda variable [52][53][54][55][56][57].…”

An Effective Approach for the Multiobjective Regional Low-Carbon Location-Routing Problem

“…Although traveling distance is a significant factor in FCCE, other parameters, especially vehicle-specific parameters and load, should be considered in the model;Govindan et al [41] presented a more detailed model by combining traveling and fixed CE of depots and manufacturers, with several coefficient matrices (e.g., uniform distribution) used to consider the effect of vehicle and load. However, these coefficient matrices are generated with uniform distribution, which does not accurately reflect FCCE; This approach was also applied in Chen et al [39] and Nakhjirkan and Rafiei [42];Validi et al [43,44,45] used fuel efficiency and distance to calculate the FCCE, like Kuo et al [17] and Poonthalir and Nadarajan [16]. Faraji and Afshar-Nadjafi [46] proposed a modified method considering the extra fuel consumption caused by carrying each extra loads.…”

“…Govindan et al [41] presented a more detailed model by combining traveling and fixed CE of depots and manufacturers, with several coefficient matrices (e.g., uniform distribution) used to consider the effect of vehicle and load. However, these coefficient matrices are generated with uniform distribution, which does not accurately reflect FCCE; This approach was also applied in Chen et al [39] and Nakhjirkan and Rafiei [42];…”

“…From the above LCLRP-based papers, four methods were used for estimating FCCE: i.e., distance-based [39,40,41,42], fuel efficiency and distance-based [5,43,44,45,46,47,48,49], load and distance-based [3,27,28,29,30,52], and microscopic [1,2,4,50]. In addition, five modes of processing FCCE can be summarized: SOM using FCCE amount [3,28,30], SOM using FCCE as a cost [1,2,4,27,29,42], SOM using FCCE as a constraint [48], MOM using FCCE as an objective [39,40,41,43,44,45,46,47,49,50,52], and MOM using FCCE as a cost [4]. With continued development and attention, the LRP with consideration of environmental effects will become a focus of future operational research.…”

Urban Mobility and City Logistics – Trends and Case Study

“…These measures show that the solutions for traffic problems do not necessarily have to be centered on improvements to the transportation network itself, but, instead, may be connected to other areas of economy. The development of models to evaluate the impact of these measures is gaining importance [16][17][18].…”