Genetic Algorithm Based Multi-objective Optimization Framework to Solve Traveling Salesman Problem

2020 ◽  
pp. 141-151 ◽  
Author(s):  
Tintu George ◽  
T. Amudha
Keyword(s):  
Genetic Algorithm ◽  
Traveling Salesman Problem ◽  
Traveling Salesman ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Optimization Framework

scholarly journals Algorithm for Multi- objective Traveling Salesman Problems based on Modified Transitive closure

2019 ◽  
Vol 9 (2) ◽  
pp. 2576-2581 ◽  
Keyword(s):  
Genetic Algorithm ◽  
Traveling Salesman Problem ◽  
Transitive Closure ◽  
Traveling Salesman ◽  
Traveling Salesman Problems ◽  
Numerical Examples ◽  
Multi Objective ◽  
Closure Method ◽  
Closure Algorithm

One of the challenging facts of the Multi Objective Traveling Salesman Problem (MOTSP) is to find the best compromised solution. In this paper, we have proposed a modified transitive closure algorithm to solve MOTSP using Genetic Algorithm (GA). Modified Transitive Closure method generates all the initial solutions of each objective. By applying Genetic Algorithm (GA), compromised solutions are obtained. Numerical examples are provided to show the efficiency of the proposed algorithm for MOTSP

A memetic random-key genetic algorithm for a symmetric multi-objective traveling salesman problem

2008 ◽  
Vol 55 (2) ◽  
pp. 439-449 ◽  
Author(s):  
Funda Samanlioglu ◽  
William G. Ferrell ◽  
Mary E. Kurz
Keyword(s):  
Genetic Algorithm ◽  
Traveling Salesman Problem ◽  
Traveling Salesman ◽  
Multi Objective

Multi-Objective Optimization of Slope Stability Using Wedge Analysis and Genetic Algorithm

2018 ◽  
pp. 221-239
Author(s):  
Sarat Kumar Das
Keyword(s):  
Genetic Algorithm ◽  
Slope Stability ◽  
Slope Angle ◽  
Seismic Zone ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Waste Containment ◽  
Multi Objective ◽  
Optimization Framework ◽  
Waste Containment Systems

Slope stability of different waste containment systems is a matter of serious concern due to its impact on air, land, and water pollution, affecting human and aquatic lives. It has been observed that most of the waste containment slope failures are translational failure. In this chapter, the slope stability analysis of the waste containment is discussed with translational failure (wedge analysis) in single and multi-objective optimization framework using genetic algorithm (GA). Non-dominated sorting genetic algorithm II (NSGA-II) is found to efficient in developing the Pareto front in terms of factor of safety (FOS), height of embankment, and volume of the failed slope. The FOS decreased with increase in height of the slope and the volume of the slope also increased. The optimized slope in terms of different slope angle and with seismic coefficients is also discussed. Such a study will help the professional in deciding the height of the slope as per the FOS in a specified seismic zone.

MULTI-OBJECTIVE OPTIMIZATION OF OFFSHORE TSUNAMI OBSERVATION POINTS BY GENETIC ALGORITHM

2020 ◽  
Vol 76 (2) ◽  
pp. I_325-I_330
Author(s):  
Kazutoshi KURAMOTO ◽  
Fumiyasu MAKINOSHIMA ◽  
Anawat SUPPASRI ◽  
Fumihiko IMAMURA
Keyword(s):  
Genetic Algorithm ◽  
Multi Objective Optimization ◽  
Multi Objective
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