ANT INTELLIGENT APPLIED TO SEWER NETWORK DESIGN OPTIMIZATION PROBLEM: USING FOUR DIFFERENT ALGORITHMS

2019 ◽  
Vol 18 (5) ◽  
pp. 957-971
Author(s):  
Ramtin Moeini
Keyword(s):  
Network Design ◽  
Design Optimization ◽  
Optimization Problem ◽  
Sewer Network

scholarly journals Feasible Sanitary Sewer Network Generation Using Graph Theory

2019 ◽  
Vol 2019 ◽  
pp. 1-15
Author(s):  
Mustafa Erkan Turan ◽  
Goksen Bacak-Turan ◽  
Tulin Cetin ◽  
Ersin Aslan
Keyword(s):  
Graph Theory ◽  
Design Optimization ◽  
Case Studies ◽  
Optimization Problem ◽  
System Optimization ◽  
Layout Optimization ◽  
Sewer System ◽  
Sanitary Sewer ◽  
Sewer Network ◽  
Hydraulic Design

A graph theory-based methodology is proposed for the sewer system optimization problem in this study. Sewer system optimization includes two subproblems: layout optimization and hydraulic design optimization, which can be solved independently or solved simultaneously. No matter which method is chosen for the solution of the optimization problem, a feasible layout that satisfies the restrictions of the sewer system must be obtained in any step of the solution. There are two different layout options encountered: the layouts containing all sewer links and the layouts not containing all sewer links. The method proposed in this study generates a feasible sewer layout that contains all sewer links and satisfies all restrictions of a sanitary sewer system by using graph theory without any additional strategies unlike other studies. The method is applied to two different case studies. The results of the case studies have shown that graph theory is well applicable to sewer system optimization and the methodology proposed based on it is capable of generating a feasible layout. This study is expected to stimulate the use of graph theory on similar studies.

scholarly journals A NETWORK DESIGN OPTIMIZATION PROBLEM FOR RO-RO FREIGHT TRANSPORT IN THE TYRRHENIAN AREA

2019 ◽  
Vol 14 (4) ◽  
pp. 63-76 ◽  
Author(s):  
Gianfranco FANCELLO ◽  
Patrizia SERRA ◽  
Simona MANCINI
Keyword(s):  
Network Design ◽  
Design Optimization ◽  
Optimization Problem ◽  
Freight Transport

The Radio Network Design Optimization Problem

2009 ◽  
pp. 219-260 ◽  
Author(s):  
Sílvio P. Mendes ◽  
Juan A. Gómez-Pulido ◽  
Miguel A. Vega-Rodríguez ◽  
Juan M. Sánchez-Pérez ◽  
Yago Sáez ◽  
...  
Keyword(s):  
Network Design ◽  
Design Optimization ◽  
Optimization Problem ◽  
Radio Network

Adaptive Complex Method for Efficient Design Optimization

2007 ◽  
Author(s):  
Marcus Pettersson ◽  
Johan O¨lvander
Keyword(s):  
Design Optimization ◽  
Optimization Problem ◽  
Global Optimum ◽  
Direct Search ◽  
Complex Method ◽  
Efficient Design ◽  
Direct Search Methods ◽  
Simulation Based ◽  
Set Of Points ◽  
Quasi Newton

Box’s Complex method for direct search has shown promise when applied to simulation based optimization. In direct search methods, like Box’s Complex method, the search starts with a set of points, where each point is a solution to the optimization problem. In the Complex method the number of points must be at least one plus the number of variables. However, in order to avoid premature termination and increase the likelihood of finding the global optimum more points are often used at the expense of the required number of evaluations. The idea in this paper is to gradually remove points during the optimization in order to achieve an adaptive Complex method for more efficient design optimization. The proposed method shows encouraging results when compared to the Complex method with fix number of points and a quasi-Newton method.

Solving a Two-stage Supply Chain Network Design Problem with Fixed Costs by a Hybrid Genetic Algorithm

2021 ◽  
Author(s):  
Ovidiu Cosma ◽  
Petrică C Pop ◽  
Cosmin Sabo
Keyword(s):  
Genetic Algorithm ◽  
Supply Chain ◽  
Network Design ◽  
Design Problem ◽  
Optimization Problem ◽  
Hybrid Genetic Algorithm ◽  
Network Design Problem ◽  
Supply Chain Network Design ◽  
Supply Chain Network ◽  
Fixed Costs

Abstract In this paper we investigate a particular two-stage supply chain network design problem with fixed costs. In order to solve this complex optimization problem, we propose an efficient hybrid algorithm, which was obtained by incorporating a linear programming optimization problem within the framework of a genetic algorithm. In addition, we integrated within our proposed algorithm a powerful local search procedure able to perform a fine tuning of the global search. We evaluate our proposed solution approach on a set of large size instances. The achieved computational results prove the efficiency of our hybrid genetic algorithm in providing high-quality solutions within reasonable running-times and its superiority against other existing methods from the literature.

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