Intelligent Differential Evolution Scheme for Network Resources in IoT

Abstract

Scheduling is a fundamental factor in managing the network resource of the Internet of things. For IoT systems such as production lines, to operate effectively, it is necessary to find an intelligent management scheme, i.e., schedule, for network resources. In this study, we focus on multiskill resource-constrained project scheduling problem (MS-RCPSP), a combinational optimization problem that has received extensive attention from the research community due to its advantages in network resource management. In recent years, many approaches have been utilized for solving this problem such as genetic algorithm and ant colony optimization. Although these approaches introduce various optimization techniques, premature convergence issue also occurs. Moreover, previous studies have only been verified on simulation data but not on real data of factories. This paper formulated the MS-RCPSP and then proposed a novel algorithm called DEM to solve it. The proposed algorithm was developed based on the differential evolution metaheuristic. Besides, we build the reallocate function to improve the solution quality so that the proposed algorithm converges rapidly to global extremum while also avoiding getting trapped in a local extremum. To evaluate the performance of the proposed algorithm, we conduct the experiment on iMOPSE, the simulated dataset used by previous authors in their research studies. In addition, DEM was verified on real dataset supported by a famous textile industry factory. Experimental results on both simulated data and real data show that the proposed algorithm not only finds a better schedule compared with related works but also can reduce the processing time of the production line currently used at the textile industry factory.

Integrating Digitalized Data and Optimization Method for Automated Production Planning in Sewing Lines

“…The subsequent sections of the article are structured as follows: Part 2 provides a comprehensive review of research pertinent to digital transformation; Part 3 delineates the methodology for integrating IoT devices in industrial garment production and the process of digitizing data related to industrial product production lines; Part 4 expounds on the scheduling problem employed for coordinating production activities based on the Real-RCPSP limited resource project scheduling problem. Part 5 empirically verifies the Real-RCPSP problem [1,2] using real data collected from TNG company. Finally, Part 6 encapsulates conclusions and outlines directions for future research.…”