Sudoku is a NP complete combinatorial number placement puzzle which has been solved using various algorithms including evolutionary algorithms. In this paper, we propose a multistage genetic algorithm (GA) for solving...
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ISBN:
(纸本)9781467399395
Sudoku is a NP complete combinatorial number placement puzzle which has been solved using various algorithms including evolutionary algorithms. In this paper, we propose a multistage genetic algorithm (GA) for solving Sudoku. In this algorithm, the group table concept has been incorporated. This work progresses with a couple of cycles. In every cycle GA works for finding better solution. The each elements of the best solution in any particular cycle undergo through a multidirectional crosscheck validation process and finally selected subject to a probability. After each cycle, group table is updated depending on the chosen elements of the best solution in the previous cycle. This algorithm also comprises of new population generation, fitness assignment with more penalization, crossover and mutation operators etc. The results show that multistage GA is competitive with good successful rate for solving various Sudoku puzzles.
Most frequent surface shapes of man-made constructions are planar surfaces. Discovering those surfaces is a big step toward extracting as-built/-is construction information from 3D point cloud. In this paper, a real-c...
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ISBN:
(纸本)9783319165486;9783319165493
Most frequent surface shapes of man-made constructions are planar surfaces. Discovering those surfaces is a big step toward extracting as-built/-is construction information from 3D point cloud. In this paper, a real-coded geneticalgorithm (GA) formulation for planar surfaces recognition in 3D point clouds is presented. The algorithm developed based on a multistage approach;thereby, it finds one planar surface (part of solution) at each stage. In addition, the logarithmically proportional objective function that is used in this approach can adapt itself to scale and spatial density of the point cloud. We tested the proposed application on a synthetic point cloud containing several planar surfaces with different shapes, positions, and with a wide variety of sizes. The results obtained showed that the proposed method is capable to find all plane's configurations of flat surfaces with a minor distance to the actual configurations.
The multiobjective route selection problem (m-RSP) is a key research topic in the car navigation system (CNS) for ITS (Intelligent Transportation System). In this paper, we propose an interactive multistage weight-bas...
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The multiobjective route selection problem (m-RSP) is a key research topic in the car navigation system (CNS) for ITS (Intelligent Transportation System). In this paper, we propose an interactive multistage weight-based Dijkstra geneticalgorithm (mwD-GA) to solve it. The purpose of the proposed approach is to create enough Pareto-optimal route's with good distribution for the car driver depending on his/her preference. At the same time, the routes can be recalculated according to the driver's preferences by the multistage framework proposed. In the solution approach proposed, the accurate route searching ability of the Dijkstra algorithm and the exploration ability of the geneticalgorithm (GA) are effectively combined together for solving the m-RSP problems. Solutions provided by the proposed approach are compared with the current research to show the effectiveness and practicability of the solution approach proposed.
This paper discusses the application of big data technology in enterprise human resource management, especially the innovative application of multi-stage geneticalgorithm in human resource management system design. T...
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