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

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

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The development of a novel multi-objective optimization framework for non-vertical well placement based on a modified non-dominated sorting genetic algorithm-II

Computational Geosciences ◽

10.1007/s10596-019-09863-2 ◽

2019 ◽

Vol 23 (5) ◽

pp. 1065-1085 ◽

Cited By ~ 2

Author(s):

Auref Rostamian ◽

Saeid Jamshidi ◽

Emily Zirbes

Keyword(s):

Genetic Algorithm ◽

Multi Objective Optimization ◽

Well Placement ◽

Vertical Well ◽

Multi Objective ◽

Optimization Framework

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

Computers & Industrial Engineering ◽

10.1016/j.cie.2008.01.005 ◽

2008 ◽

Vol 55 (2) ◽

pp. 439-449 ◽

Cited By ~ 38

Author(s):

Funda Samanlioglu ◽

William G. Ferrell ◽

Mary E. Kurz

Keyword(s):

Genetic Algorithm ◽

Traveling Salesman Problem ◽

Traveling Salesman ◽

Multi Objective

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

Advances in Computational Intelligence and Robotics - Handbook of Research on Predictive Modeling and Optimization Methods in Science and Engineering ◽

10.4018/978-1-5225-4766-2.ch010 ◽

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.

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