An Adaptive Genetic Algorithm Based on Multi-Population Parallel Evolutionary for Highway Alignment Optimization Model

Based on the characteristics of the highway design, this paper transfers all the factors involved in the highway design to a cost-optimized-oriented model and designs a variety parallel genetic algorithm to optimize highway design. While maintaining evolution stability of excellent individual, the algorithm can improve convergence rate and accuracy and avoid premature convergence generated by single-population evolution. To some extent, it makes up generalization-lacking defects of a single species or steady parameters in premature overcoming. Finally, the algorithm is verified with a good result. This algorithm provides a useful method for highway design.

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Multi-objective highway alignment optimization using a genetic algorithm

Journal of Advanced Transportation ◽

10.1002/atr.5670430405 ◽

2009 ◽

Vol 43 (4) ◽

pp. 481-504 ◽

Cited By ~ 19

Author(s):

Avijit Maji ◽

Manoj K. Jha

Keyword(s):

Genetic Algorithm ◽

Multi Objective ◽

Highway Alignment Optimization ◽

Highway Alignment

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An Improved Adaptive Genetic Algorithm for Two-Dimensional Rectangular Packing Problem

Applied Sciences ◽

10.3390/app11010413 ◽

2021 ◽

Vol 11 (1) ◽

pp. 413

Author(s):

Yi-Bo Li ◽

Hong-Bao Sang ◽

Xiang Xiong ◽

Yu-Rou Li

Keyword(s):

Genetic Algorithm ◽

Packing Problem ◽

Global Perspective ◽

Adaptive Genetic Algorithm ◽

Two Dimensional ◽

Filling Rate ◽

Zero Waste ◽

Population Evolution ◽

Rectangular Packing ◽

The Impact

This paper proposes the hybrid adaptive genetic algorithm (HAGA) as an improved method for solving the NP-hard two-dimensional rectangular packing problem to maximize the filling rate of a rectangular sheet. The packing sequence and rotation state are encoded in a two-stage approach, and the initial population is constructed from random generation by a combination of sorting rules. After using the sort-based method as an improved selection operator for the hybrid adaptive genetic algorithm, the crossover probability and mutation probability are adjusted adaptively according to the joint action of individual fitness from the local perspective and the global perspective of population evolution. The approach not only can obtain differential performance for individuals but also deals with the impact of dynamic changes on population evolution to quickly find a further improved solution. The heuristic placement algorithm decodes the rectangular packing sequence and addresses the two-dimensional rectangular packing problem through continuous iterative optimization. The computational results of a wide range of benchmark instances from zero-waste to non-zero-waste problems show that the HAGA outperforms those of two adaptive genetic algorithms from the related literature. Compared with some recent algorithms, this algorithm, which can be increased by up to 1.6604% for the average filling rate, has great significance for improving the quality of work in fields such as packing and cutting.

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Potentialities of a Highway Alignment Optimization Method in an I-BIM Environment

Periodica Polytechnica Civil Engineering ◽

10.3311/ppci.12220 ◽

2019 ◽

Cited By ~ 1

Author(s):

Nicola Bongiorno ◽

Gaetano Bosurgi ◽

Federico Carbone ◽

Orazio Pellegrino ◽

Giuseppe Sollazzo

Keyword(s):

Optimal Solution ◽

Optimization Method ◽

Information Modeling ◽

Design Solution ◽

Shared Environment ◽

Highway Design ◽

Time Interaction ◽

Building Information ◽

Highway Alignment Optimization ◽

Highway Alignment

The BIM (Building Information Modeling) approach potential in the civil engineering field opened novel scenarios in the design idea concept, from planning to executive and constructive phases. The related advantages are numerous and not only limited to a real-time interaction among the involved subjects, that can actually operate in an optimized 3D shared environment. Owing to the sharing information philosophy and to the features of various "smart objects" combined in the project, this innovation reduces potential errors and increases the effectiveness of the design solution in terms of both functionality and cost. Despite these advantages, the highway alignment design problem remains very complicated and not easy to solve without appropriate supporting tools. In recent years, several efforts have been spent in defining highway optimization procedures for helping designers in the selection of an optimal solution in compliance with numerous different constraints. Introducing these procedures in a BIM environment may represent a crucial step in the improvement of the highway design procedures, exploiting the full representation and modelling potential of the approach. In this paper, the authors present the advantages of a 3D highway alignment optimization algorithm, based on the Particle Swarm Optimization method, and its possible implementation in a BIM platform. A proper I-BIM environment can exploit the potential of the alignment optimization algorithms, simplifying the analysis of the different solutions, the final representation and the eventual manual modifications.

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Research on Logistic Path Planning Strategy Based on Coarse-Grained Parallel Genetic Algorithm

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.798-799.920 ◽

2013 ◽

Vol 798-799 ◽

pp. 920-923

Author(s):

Wu Xue Jiang ◽

Xuan Zi Hu ◽

Min Xia Liu ◽

Peng Fei Yin

Keyword(s):

Genetic Algorithm ◽

Path Planning ◽

Convergence Rate ◽

Route Planning ◽

Planning System ◽

Coarse Grained ◽

Parallel Genetic Algorithm ◽

Planning Strategy ◽

Elitist Strategy ◽

Implementation Steps

In order to minimize the precocity and deceit happened in genetic algorithm, this thesis puts forward an improved intelligent evolutionary algorithmcoarse-grained parallel genetic algorithm which proposes schema order based cross operator, task immigration based cross operator, and improved approach for elitist strategy. Also, this paper applies the algorithm into logistic route planning system to clarify the concrete implementation steps for coding, population generation and genetic operator. According to experiment result, the improved algorithm mentioned in this assay have advanced the convergence rate and optimizing ability to some extent.

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