A hybrid Genetic Algorithm approach to minimize the total joint cost of a single-vendor multi-customer integrated scheduling problem
A hybrid Genetic Algorithm approach to minimize the total joint cost of a single-vendor multi-customer integrated scheduling problem
- New search for: Grunder, Olivier
- New search for: Hammoudan, Zakaria
- New search for: Beroule, Benoit
- New search for: Barakat, Oussama
- New search for: Grunder, Olivier
- New search for: Hammoudan, Zakaria
- New search for: Beroule, Benoit
- New search for: Barakat, Oussama
This paper addresses the scheduling of supply chains with interrelated factories consisting of a single vendor and multiple customers. In this research, one transporter is available to deliver jobs from vendor to customers, and the jobs can be processed by batch. The problem studied in this paper focuses on a real-case scheduling problem of a multi-location hospital supplied with a central pharmacy. The objective of this work is to minimize the total cost, while satisfying the customer’s due dates constraints. A mathematical formulation of the problem is given as a Mixed Integer Programming model. Then, a Branch-and-Bound algorithm is proposed as an exact method for solving this problem, a greedy local search is developed as a heuristic approach, and a hybrid Genetic Algorithm is presented as a meta-heuristic. Computation experiments are conducted to highlight the performance of the proposed methods.
Document information
A hybrid Genetic Algorithm approach to minimize the total joint cost of a single-vendor multi-customer integrated scheduling problem
Transportation Planning and Technology ; 42 , 6 ; 625-642
2019-08-18
18 pages
Article (Journal)
Electronic Resource
English
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