TAILIEUCHUNG - Bi-objective freight scheduling optimization in an integrated forward/reverse logistic network using non-dominated sorting genetic algorithm-II

This research proposes a model to optimize a freight-scheduling problem. The proposed model of this paper based on Non-dominated sorting genetic algorithm-II is formulated to solve a conflicting bi-objective optimization and optimizes a real-world case study. | Bi-objective freight scheduling optimization in an integrated forward reverse logistic network using non-dominated sorting genetic algorithm-II Decision Science Letters 9 2020 91 106 Contents lists available at GrowingScience Decision Science Letters homepage dsl Bi-objective freight scheduling optimization in an integrated forward reverse logistic network using non-dominated sorting genetic algorithm-II Taufik Djatnaa and Guritno A. M. Amienb a Post Graduate Program Department of Agro-industrial Technology IPB University Bogor Indonesia bDepartment of Agro-industrial Technology IPB University Bogor Indonesia CHRONICLE ABSTRACT Article history Simultaneous products distribution and items retrieval in an integrated forward reverse logistics Received June 15 2019 network faces a complex freight-scheduling problem due to the constraints involved. In the high Received in revised format to intermediate network level the problem usually exists in the form of single stop transportation. June 20 2019 To reach a higher level of performances there is a need to model and optimize the freight Accepted July 27 2019 Available online schedule. This research proposes a model to optimize a freight-scheduling problem. The July 27 2019 proposed model of this paper based on Non-dominated sorting genetic algorithm-II is formulated Keywords to solve a conflicting bi-objective optimization and optimizes a real-world case study. A solution Bi-objective optimization from the model demonstrates the solution interpretation in the form of delivery schedule Freight scheduling distribution as well as retrieval route and vehicle assignment. Moreover the solutions are also Integrated forward reverse comparable to some current manual solution by its similarity. The results show that the model logistic network was capable of generating feasible solutions while satisfying all of its constraints. Non-dominated sorting genetic algorithm-II 2020 by the authors licensee Growing

• Cơ khí - Chế tạo máy
• Bi objective optimization
• Integrated forward/reverse logistic network
• Non dominated sorting genetic algorithm II
• Non dominated sorting genetic algorithm II
• Bi objective freight scheduling optimization