Genetic Algorithms–Based Network Optimization System with Multiple Objectives

2007 ◽  
Vol 2016 (1) ◽  
pp. 85-95 ◽  
Author(s):  
Kelvin C. P. Wang ◽  
Vu Nguyen ◽  
John P. Zaniewski
Keyword(s):  
Genetic Algorithms ◽  
Network Optimization ◽  
Multiple Objectives ◽  
Optimization System

Parallel Single and Multiple Objectives Genetic Algorithms

2013 ◽  
pp. 73-110
Author(s):  
B. S. P. Mishra ◽  
S. Dehuri ◽  
R. Mall ◽  
A. Ghosh
Keyword(s):  
Genetic Algorithms ◽  
Processing Time ◽  
Multiple Objectives ◽  
Multiple Objective ◽  
Acceptable Solution ◽  
Multi Objective ◽  
Potential Applications

This paper critically reviews the reported research on parallel single and multi-objective genetic algorithms. Many early efforts on single and multi-objective genetic algorithms were introduced to reduce the processing time needed to reach an acceptable solution. However, some parallel single and multi-objective genetic algorithms converged to better solutions as compared to comparable sequential single and multiple objective genetic algorithms. The authors review several representative models for parallelizing single and multi-objective genetic algorithms. Further, some of the issues that have not yet been studied systematically are identified in the context of parallel single and parallel multi-objective genetic algorithms. Finally, some of the potential applications of parallel multi-objective GAs are discussed.

Pavement Performance-Oriented Network Optimization System

1996 ◽  
Vol 1524 (1) ◽  
pp. 86-93 ◽  
Author(s):  
Fengxian Liu ◽  
Kelvin C. P. Wang
Keyword(s):  
Decision Support ◽  
Network Optimization ◽  
Performance Standards ◽  
Pavement Performance ◽  
Department Of Transportation ◽  
Planning Period ◽  
Pavement Condition ◽  
Optimization System ◽  
Performance Requirements ◽  
Annual Budget

The objective of the current network optimization system (NOS) model used by the Arizona Department of Transportation is to minimize the annual cost over the planning period. An NOS model with the objective of maximizing a network's pavement performance is presented. In this performance-oriented NOS, the annual budget is given as a constraint that is distributed evenly over the planning period. This NOS model aims to provide an approach simulating a possible scenario in a state department of transportation by effectively using a given budget in the planning period. At the same time the performance of the pavement network is also maximized. In relation to annual budget and pavement condition, two types of analysis are conducted: in the first analysis, only annual budget is applied as the constraint for this model; in the second, both annual budget and pavement performance requirements are introduced as the constraints. The necessary minimum annual budgets for various pavement performance requirements are compared; using the results, a rational annual budget for the needed pavement performance standards can be obtained, which may be used as decision support data for future budget allocation.

Sign in / Sign up

Export Citation Format

Share Document