A survey of meta-heuristic methods for optimization problems
محورهای موضوعی : محاسبات تکاملی
Mehdi Fazli
1
,
somayyeh faraji
2
1 - Department of Mathematics, Ardabil Branch, Islamic Azad University, Ardabil, Iran
2 - 1Department of Mathematics, Islamic Azad University, Tabriz Branch, Tabriz, Iran
کلید واژه: Operations research, Meta-heuristic, Hybridization, Memetic algorithm,
چکیده مقاله :
In this article, we will examine the problems related to routing and positioning with real variables and examine the related questions. These engineering, inventory and optimization decisions are made in a multi-layered supply chain system, including suppliers, warehouses and different buyers. We are looking for new ways to manage location and routing efficiently and effectively. In order to increase efficiency and achieve optimal results, exploratory and meta-heuristic methods have been used. In meta-heuristic techniques, a combination technique is usually used to increase performance. Therefore, this review article examines meta-heuristic methods and analysis of location problems using different quantities. It also examines the advantages and disadvantages of each method to optimally solve these problems in order to introduce practical and efficient methods.
In this article, we will examine the problems related to routing and positioning with real variables and examine the related questions. These engineering, inventory and optimization decisions are made in a multi-layered supply chain system, including suppliers, warehouses and different buyers. We are looking for new ways to manage location and routing efficiently and effectively. In order to increase efficiency and achieve optimal results, exploratory and meta-heuristic methods have been used. In meta-heuristic techniques, a combination technique is usually used to increase performance. Therefore, this review article examines meta-heuristic methods and analysis of location problems using different quantities. It also examines the advantages and disadvantages of each method to optimally solve these problems in order to introduce practical and efficient methods.
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