Abstract
Genetic algorithm (i.e., GA) has longtermly obtained an extensive recognition for solving the optimization problem. Its pipelines process, which involves several operations, has been applied in many NP-hard problems, including the transportation network design problem (i.e., TNDP). As part of evolutionary computation methods, GA is inspired by Darwinian evolution, which is relied on the genetic operators (i.e., recombination, and mutation). On other side, the considerably achievement has been acquired by the genome researches, which offers an opportunity to deeply explore the recombination and mutation processes. This paper then presents variants of GA, which are inspired by the recent genome evidence of genetic operators. This exploration expectantly extends the benefit of evolution-based algorithm, which has been shown by the previous finding of GA. For examining the performance of proposed GA, the numerical experiment is involved for solving the TNDP. The performance comparisons show that the variation of crossover rate within a certain group of population provide better result than the standard GA.
Highlights
The considerable growth on traffic has delivered a numerous problem, which forces the decision maker to develop the transportation network (TN)
Based on the above review on the current genome evidence, it can be inferred that the exploration can be taken place in the two parts, namely: a) Crossover rate, which is currently set in the similar number for all individual, might be arranged to be varied for each individual based on the specific characteristics. b) Mutation processes, which is relied on the SNP approach, may be investigated by applying “inserting” based approach
Metaheuristic-based approaches are practically invoked to handle this problem, including Genetic Algorithm (GA) with its recombination and mutation operators. Such operators are inspired by the natural processes of organism genome, which has achieved a remarkable development in recent years
Summary
The considerable growth on traffic has delivered a numerous problem, which forces the decision maker to develop the transportation network (TN). Model for designing TN is required for efficiently allocating the budgets, which is practically proposed within the framework of TN design problem (TNDP). To solve TNDP, several metaheuristic-based approaches have been proposed. The component and structure of GA have been expansively developed, recombination and mutation operators have been positioned as a basic operator assembled in GA processes. Recombination operator mimics the mating process to produce offspring, while the mutation operators represent the possibility of random change in the chromosome. In line with the GA development, the availability of new molecular technology has permitted to provide the more information relating to the genome natural process (e.g., recombination and mutation), which may be different from that previously available. We continue with discussion relating to the application of GA-based approach for solving TNDP and the GA performance investigation. In last section, there is a summary of the methodologies, results, and analyses used in this paper
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