Simultaneous optimization of operational and financial decisions to closed-loop supply chain network under uncertainty
| Autor: | Majid Ramezani, Ali Mohammad Kimiagari |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Finance
Rate of return 0209 industrial biotechnology business.industry Mechanical Engineering media_common.quotation_subject Supply chain Robust optimization 02 engineering and technology Industrial and Manufacturing Engineering Accounts payable Microeconomics 020901 industrial engineering & automation Cash 0202 electrical engineering electronic engineering information engineering Economics 020201 artificial intelligence & image processing Cash flow Supply chain network business Accounts receivable media_common |
| Zdroj: | Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture. 230:1910-1924 |
| ISSN: | 2041-2975 0954-4054 |
| DOI: | 10.1177/0954405415578723 |
| Popis: | This article integrates the company operations decisions (i.e. location, production, inventory, distribution, and transportation) and finance decisions (i.e. cash, accounts payable and receivable, debt, securities, payment delays, and discounts) in which the demands and return rate are uncertain, defined by a set of scenarios. The cash flow and budgeting model will be coupled with supply chain network design using a mixed integer linear programming formulation. The article evaluates two financial criteria, that is, the change in equity and the profit as objective functions. The results indicate that objective functions are partially interdependent, that is, they conflict in certain parts. This fact illustrates the inadequacy of treating process operations and finances in isolated environments and pursuing objective myopic performance indicators such as profit or cost. Due to the importance of the supply chain network design problem, a multi-objective robust optimization with the max–min version is extended to cope with the uncertainty. A solution approach integrating Benders’ decomposition method with the scenario relaxation algorithm is also proposed in this research. The improved algorithm has been applied to solve a number of numerical experiments. All results illustrate significant improvement in computation time of the improved algorithm over existing approaches. For a problem, the proposed algorithm shows a significant reduction in computational time compared with the Benders’ decomposition and scenario relaxation that shows the efficiency of the proposed solution method. |
| Databáze: | OpenAIRE |
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