scholarly journals A multiobjective optimization framework for multicontaminant industrial water network design

2011 ◽  
Vol 92 (7) ◽  
pp. 1802-1808 ◽  
Author(s):  
Marianne Boix ◽  
Ludovic Montastruc ◽  
Luc Pibouleau ◽  
Catherine Azzaro-Pantel ◽  
Serge Domenech
Keyword(s):  
Multiobjective Optimization ◽  
Network Design ◽  
Industrial Water ◽  
Water Network ◽  
Optimization Framework

scholarly journals Multiobjective Optimization Using Goal Programming for Industrial Water Network Design

2014 ◽  
Vol 53 (45) ◽  
pp. 17722-17735 ◽  
Author(s):  
Manuel A. Ramos ◽  
Marianne Boix ◽  
Ludovic Montastruc ◽  
Serge Domenech
Keyword(s):  
Multiobjective Optimization ◽  
Network Design ◽  
Goal Programming ◽  
Industrial Water ◽  
Water Network

A holistic optimization framework for forest machine trail network design accounting for multiple objectives and machines

2019 ◽  
Vol 49 (2) ◽  
pp. 111-120 ◽  
Author(s):  
Ahmad Hosseini ◽  
Ola Lindroos ◽  
Eddie Wadbro
Keyword(s):  
Network Design ◽  
Multiple Objectives ◽  
Optimization Framework ◽  
Trade Offs ◽  
Design Changes ◽  
Optimal Network Design ◽  
Optimal Network ◽  
Ecological Objectives ◽  
Holistic Optimization ◽  
The Impact

Ground-based mechanized forestry requires the traversal of terrain by heavy machines. The routes that they take are often called “machine trails” and are created by removing trees from the trail and placing the logs outside it. Designing an optimal machine trail network is a complex locational problem that requires understanding how forestry machines can operate on the terrain, as well as the trade-offs between various economic and ecological aspects. Machine trail designs are currently created manually based on intuitive decisions about the importance, correlations, and effects of many potentially conflicting aspects. Badly designed machine trail networks could result in costly operations and adverse environmental impacts. Therefore, this study was conducted to develop a holistic optimization framework for machine trail network design. Key economic and ecological objectives involved in designing machine trail networks for mechanized cut-to-length operations are presented, along with strategies for simultaneously addressing multiple objectives while accounting for the physical capabilities of forestry machines, the impact of slope, and the operating costs. Ways of quantitatively formulating and combining these different aspects are demonstrated, together with examples showing how the optimal network design changes in response to various inputs.

scholarly journals An Airway Network Flow Assignment Approach Based on an Efficient Multiobjective Optimization Framework

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Xiangmin Guan ◽  
Xuejun Zhang ◽  
Yanbo Zhu ◽  
Dengfeng Sun ◽  
Jiaxing Lei
Keyword(s):  
Genetic Algorithm ◽  
Multiobjective Optimization ◽  
Network Flow ◽  
Optimization Problems ◽  
Parallel Evolution ◽  
Dynamic Adjustment ◽  
Cooperative Coevolution ◽  
Solution Quality ◽  
Optimization Framework ◽  
Flow Assignment

Considering reducing the airspace congestion and the flight delay simultaneously, this paper formulates the airway network flow assignment (ANFA) problem as a multiobjective optimization model and presents a new multiobjective optimization framework to solve it. Firstly, an effective multi-island parallel evolution algorithm with multiple evolution populations is employed to improve the optimization capability. Secondly, the nondominated sorting genetic algorithm II is applied for each population. In addition, a cooperative coevolution algorithm is adapted to divide the ANFA problem into several low-dimensional biobjective optimization problems which are easier to deal with. Finally, in order to maintain the diversity of solutions and to avoid prematurity, a dynamic adjustment operator based on solution congestion degree is specifically designed for the ANFA problem. Simulation results using the real traffic data from China air route network and daily flight plans demonstrate that the proposed approach can improve the solution quality effectively, showing superiority to the existing approaches such as the multiobjective genetic algorithm, the well-known multiobjective evolutionary algorithm based on decomposition, and a cooperative coevolution multiobjective algorithm as well as other parallel evolution algorithms with different migration topology.

scholarly journals A Data-Driven Multiobjective Optimization Framework for Hyperdense 5G Network Planning

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 169423-169443
Author(s):  
Beneyam Berehanu Haile ◽  
Edward Mutafungwa ◽  
Jyri Hamalainen
Keyword(s):  
Multiobjective Optimization ◽  
Network Planning ◽  
Data Driven ◽  
Optimization Framework ◽  
5G Network
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