Investigating Modeling and Solving a Hybrid Problem Considering the Simultaneous Loading and Delivery of the Vehicle and the Locating of Facilities for Storing and Recycling in a Three-Level Green Supply Chain

Mohammad Afsharniya, Behrouz Abbasi


Today, In this research, we intend to study the modeling and solving a hybrid problem considering the simultaneous loading and delivery of the vehicle and the locating of facilities for storing and recycling in a three-level green supply chain. This issue is known as 3-level mapping routing issue in the subject literature. With the goal of presenting a mathematical model for the vehicle routing problem and locating the storage facilities and recycling facilities in a green supply chain network, an efficient algorithm is developed to optimize the problem and compare the performance of the algorithm with known algorithms such as genetics. Also one of the other purposes is to find a combination of truck and facility paths so that results in minimum transfer costs in a direct and reverse manner. By reviewing the recent articles and discovering the existing research gap, we will develop a problem model with a specific application, and eventually we will overwrite the problem in the framework of the language of the meta-innovative algorithms to solve the problem by the meta-innovative method. To compare the efficiency of the meta-innovative algorithm developed in this research and its validation, we will compare the results with a precise method using GAMS software for small issues. Also, one of the genetic algorithms can be used to test the performance of the algorithm. This research is considered within the framework of applied research regarding the orientation, because using the results of this study, some suggestions can be made to solve specific problems in the organization. In addition, this research is a descriptive method in which mathematical and modeling tools are used.

Keywords: Logistic Network, Green Supply Chain, Locating and Routing Problem, Combined or Hybrid Meta-Innovative Algorithm

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ISSN (Paper)2224-6096 ISSN (Online)2225-0581

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