Hybridizing ant colony optimization algorithm with nonlinear programming method for effective optimal design of sewer networks

2019 ◽  
Vol 91 (4) ◽  
pp. 300-321 ◽  
Author(s):  
Ramtin Moeini ◽  
Mohammad Hadi Afshar
Keyword(s):  
Nonlinear Programming ◽  
Optimal Design ◽  
Ant Colony Optimization ◽  
Optimization Algorithm ◽  
Programming Method ◽  
Ant Colony ◽  
Ant Colony Optimization Algorithm ◽  
Nonlinear Programming Method ◽  
Sewer Networks

Modeling and optimizing logistics, information, economic and financial intercluster cooperation using the ant colony optimization algorithm

2020 ◽  
Vol 26 (11) ◽  
pp. 2427-2447
Author(s):  
S.N. Yashin ◽  
E.V. Koshelev ◽  
S.A. Borisov
Keyword(s):  
Ant Colony Optimization ◽  
Optimization Algorithm ◽  
Population Decline ◽  
Innovation System ◽  
Federal District ◽  
Original Model ◽  
Ant Colony ◽  
Industrial Agglomeration ◽  
Ant Colony Optimization Algorithm

Subject. This article discusses the issues related to the creation of a technology of modeling and optimization of economic, financial, information, and logistics cluster-cluster cooperation within a federal district. Objectives. The article aims to propose a model for determining the optimal center of industrial agglomeration for innovation and industry clusters located in a federal district. Methods. For the study, we used the ant colony optimization algorithm. Results. The article proposes an original model of cluster-cluster cooperation, showing the best version of industrial agglomeration, the cities of Samara, Ulyanovsk, and Dimitrovgrad, for the Volga Federal District as a case study. Conclusions. If the industrial agglomeration center is located in these three cities, the cutting of the overall transportation costs and natural population decline in the Volga Federal District will make it possible to qualitatively improve the foresight of evolution of the large innovation system of the district under study.

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