Genetic Algorithms and the Corridor Location Problem: Multiple Objectives and Alternative Solutions

2008 ◽  
Vol 35 (1) ◽  
pp. 148-168 ◽  
Author(s):  
Xingdong Zhang ◽  
Marc P Armstrong
Keyword(s):  
Genetic Algorithms ◽  
Location Problem ◽  
Multiple Objectives ◽  
Corridor Location ◽  
Alternative Solutions

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.

An interface for exploring spatial alternatives for a corridor location problem

1992 ◽  
Vol 18 (8) ◽  
pp. 1095-1105 ◽  
Author(s):  
Richard L. Church ◽  
Scott R. Loban ◽  
Kristi Lombard
Keyword(s):  
Location Problem ◽  
Corridor Location

Genetic Algorithms with multiple objectives

1998 ◽  
Author(s):  
Erik Schaumann ◽  
Richard Balling ◽  
Kirstin Day
Keyword(s):  
Genetic Algorithms ◽  
Multiple Objectives

scholarly journals HOW TO INVEST IN BELGIAN SHARES BY MULTIMOORA OPTIMIZATION

2013 ◽  
Vol 14 (5) ◽  
pp. 940-956 ◽  
Author(s):  
Willem K. M. Brauers ◽  
Romualdas Ginevičius
Keyword(s):  
Reference Point ◽  
Point Theory ◽  
Multiple Objectives ◽  
Ratio Analysis ◽  
Multi Objective Optimization ◽  
Dimensionless Numbers ◽  
Multi Objective ◽  
Multiplicative Form ◽  
Objective Reference ◽  
Alternative Solutions

Different multiple objectives expressed in different units make optimization difficult. Therefore, the internal mechanical solution of a Ratio System, producing dimensionless numbers, is preferred to weights, which are most of the time used to compare the different units. In addition, the ratio system creates the opportunity to use a second approach: a non-subjective Reference Point Theory. Therefore, the Reference Point Theory uses the ratios found in the ratio system as co-ordinates for the alternative solutions, which are then compared to a Maximal Objective Reference Point. The two approaches form a control on each other. This overall theory is called MOORA (Multi-Objective Optimization by Ratio Analysis). The results are still more convincing if a Full Multiplicative Form is added, three methods assembled under the name of MULTIMOORA. At that moment, the control by three different approaches forms a guaranty for a solution being as non-subjective as possible. As to calculate the sum of three obtained ranks is not allowed, a theory of Ordinal Dominance is developed in order to remain in the ordinal sphere.

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