[PDF] Top 20 An Improved Genetic Algorithm for Crew Pairing Optimization

... Different genetic algorithm implementations were de- veloped to solve set-covering ...a crew pairing algorithm based on reference [4] and re- ported good ...the crew ... See full document

... In most cases, similar to the optimal solution of the single-objective doesn’t exist in multi-objective optimization problems, only exists Pareto optimal solution set. The Pareto optimal solution of multi- ... See full document

... Swarm Optimization (PSO) [7] for JPEG images, Immune Programming Algorithm (IP) [8] or Genetic Algorithm Optimization priority adjustment ... See full document

... combinatorial optimization problem such as the traveling salesman problem (TSP), the quadratic assignment problem, the vehicle routing problem, and the job-shop scheduling ...Colony Optimization (ACO), ... See full document

... the optimization of the multi-join query process of distributed database, which is mainly based on the computer time or resource cost and search strategy of querying ...programming algorithm (DPA), ... See full document

... The improved automatic ant colony genetic algorithm can help to solve the problems about schedule-time ...the improved ant colony genetic algorithm is suitable for solving the ... See full document

... Keywords: Microgrid; Multi-timescale; Collaborative Optimization; Time-sequence Property; Improved Adaptive Genetic Algorithm IAGA.. Introduction The smart grid is not exactly same as a [r] ... See full document

... ABC) Algorithm for Continuous Optimization ...(ABC) algorithm to progress its local search ability and convergence ...from Genetic Algorithm (GA) with original ABC ...deployment ... See full document

... be improved without simultaneously degrading at least one ...to optimization and search problems. Genetic algorithms belong to the larger class of evolutionary algorithms (EA), generates solution to ... See full document

... multi-objective optimization design of it. In the process of optimization, the simple genetic algorithm was improved through adjusting the crossover probability and mutation ... See full document

... Distribution system reconfiguration for loss reduction was first proposed by Merlin [2]. The network reconfiguration is carried out by changing the status (on/off) of the sectionalizing switches and tie-switches. ... See full document

... network optimization, the optimal robust solution of hub-spoke network is obtained under the condition of multiple possibilities of demand and cost, and an optimization method based on multi-objective ... See full document

... The rapid development of computer network technology and the popularization of its application in various fields lead to the more and more complex networks. For this reason, an optimization approach and ... See full document

... multi-objective optimization problems: such as Ant Colony algorithm, COA (Cuckoo Algorithm, Genetic algorithm, particle swarm optimization algorithm, fuzzy ... See full document

... colony algorithm stimulates the process through artificial ...colony algorithm is an auto catalytic reinforcement learning algorithm based on Monte Carlo, and it is also a constructive ... See full document

... is fixed, which influences algorithm speed. (c) The popu- lation is single. If there exists some individual whose fitness is more outstanding in the initial population, then it’s easy to converge to the local ... See full document

... genetic algorithm designed for the solution of the crew- scheduling problem in the rail-freight ...While genetic algorithms are capable of handling large data sets, they are prone to stalled ... See full document

... A new evolutionary algorithm called exchange market algorithm (EMA) was proposed by Naser Ghorbani and Ebrahim Babaei in 2014 [16]. The EMA is inspired by intelligent dealings of shareholders. The exchange ... See full document

... [6]. Genetic algorithms are a population based mechanism, which is used to explore the search space better than other searching algorithms especially for problems that are ...NP-hard. Genetic algorithms ... See full document

... phase shifter using a pair of multi-section radial transmission-line (TL) stubs is proposed in [3]. Global optimization is performed using the TL model followed by a local optimization based on a more ... See full document