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  • Open Access


    Rules Mining-Based Gene Expression Programming for the Multi-Skill Resource Constrained Project Scheduling Problem

    Min Hu1,2,3, Zhimin Chen4, Yuan Xia4, Liping Zhang1,2,3,*, Qiuhua Tang1,2,3

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2815-2840, 2023, DOI:10.32604/cmes.2023.027146

    Abstract The multi-skill resource-constrained project scheduling problem (MS-RCPSP) is a significant management science problem that extends from the resource-constrained project scheduling problem (RCPSP) and is integrated with a real project and production environment. To solve MS-RCPSP, it is an efficient method to use dispatching rules combined with a parallel scheduling mechanism to generate a scheduling scheme. This paper proposes an improved gene expression programming (IGEP) approach to explore newly dispatching rules that can broadly solve MS-RCPSP. A new backward traversal decoding mechanism, and several neighborhood operators are applied in IGEP. The backward traversal decoding mechanism dramatically reduces the space complexity in… More > Graphic Abstract

    Rules Mining-Based Gene Expression Programming for the Multi-Skill Resource Constrained Project Scheduling Problem

  • Open Access


    An Evolutionary Algorithm for Non-Destructive Reverse Engineering of Integrated Circuits

    Huan Zhang1,2, Jiliu Zhou1,2,*, Xi Wu2

    CMES-Computer Modeling in Engineering & Sciences, Vol.127, No.3, pp. 1151-1175, 2021, DOI:10.32604/cmes.2021.015462

    Abstract In hardware Trojan detection technology, destructive reverse engineering can restore an original integrated circuit with the highest accuracy. However, this method has a much higher overhead in terms of time, effort, and cost than bypass detection. This study proposes an algorithm, called mixed-feature gene expression programming, which applies non-destructive reverse engineering to the chip with bypass detection data. It aims to recover the original integrated circuit hardware, or else reveal the unknown circuit design in the chip. More >

  • Open Access


    Soil Moisture Prediction in Peri-urban Beijing, China: Gene Expression Programming Algorithm

    Hongfei Niu1,2, Fanyu Meng3, Huanfang Yue3, Lihong Yang4, Jing Dong2,5, Xin Zhang2,5,*

    Intelligent Automation & Soft Computing, Vol.28, No.1, pp. 93-106, 2021, DOI:10.32604/iasc.2021.010131

    Abstract Soil moisture is an important indicator for agricultural planting and agricultural water management. People have been trying to guide crop cultivation, formulate irrigation systems, and develop intelligent agriculture by knowing exactly what the soil moisture is in real time. This paper considers the impact of meteorological parameters on soil-moisture change and proposes a soil-moisture prediction method based on the Gene Expression Programming (GEP) algorithm. The prediction model is tested on datasets from Shunyi, Yanqing and Daxing agricultural farms, Beijing. The results show that the GEP model can predict soil moisture with a maximum correlation coefficient of 0.98, and the root-mean-square… More >

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