Optimization Problems And Genetic Algorithms

Dynamics of Genetic Algorithms in Optimization Problems

In a recent paper [1], some of us have studied the dynamics of the Monte Carlo simulation algorithm in several very different optimization problems. The optimization problems that were investigated in [1] include the travelling salesman problem (TSP) [2], the lattice version of the protein folding problem (PFP) [3], x-ray data analysis (XDA) and a multi-variable function. In the above studied c...

Optimization of teacher volunteer transferring problems using greedy genetic algorithms

In this paper, an evolutionary approach based on a greedy genetic algorithm (GA) is studied to serve as an efficient solver for real world teacher volunteer transferring problems (TVTPs). In the proposed approach, the transferring problems are first mathematically formulated into constrained combinational optimization problems and then, an improved neighborhood-search based on greedy search rul...

Multiobjective Optimization Genetic Algorithms for Domestic Airline Crew Pairing Problems

Airline crew pairing problems involve assigning the required crew members to each flight segment in a given time period, while complying with a variety of work regulations and collective agreements. Traditional researches formulate the pairing problems as integer programming problems, and use deterministic approaches to optimize the solutions. Such these approaches usually suffer from some crit...

Efficient Genetic Algorithms for Solving Hard Constrained Optimization Problems

Statistical Design of Genetic Algorithms for Combinatorial Optimization Problems

Many genetic algorithms GA have been applied to solve different NP-complete combinatorial optimization problems so far. The striking point of using GA refers to selecting a combination of appropriate patterns in crossover, mutation, and and so forth and fine tuning of some parameters such as crossover probability, mutation probability, and and so forth. One way to design a robust GA is to selec...