Abstract
This paper defines and introduces the formulation of the Real-RCPSP (Real-Resource-Constrained Project Scheduling Problem), a new variant of the MS-RCPSP (Multiskill Resource-Constrained Project Scheduling Problem). Real-RCPSP is an optimization problem that has been attracting widespread interest from the research community in recent years. Real-RCPSP has become a critical issue in many fields such as resource allocation to perform tasks in Edge Computing or arranging robots at industrial production lines at factories and IoT systems. Compared to the MS-RCPSP, the Real-RCPSP is supplemented with assumptions about the execution time of the task, so it is more realistic. The previous algorithms for solving the MS-RCPSP have only been verified on simulation data, so their results are not completely convincing. In addition, those algorithms are designed only to solve the MS-RCPSP, so they are not completely suitable for solving the new Real-RCPSP. Inspired by the Cuckoo Search approach, this literature proposes an evolutionary algorithm that uses the function Reallocate for fast convergence to the global extremum. In order to verify the proposed algorithm, the experiments were conducted on two datasets: (i) the iMOPSE simulation dataset that previous studies had used and (ii) the actual TNG dataset collected from the textile company TNG. Experimental results on the iMOPSE simulation dataset show that the proposed algorithm achieves better solution quality than the existing algorithms, while the experimental results on the TNG dataset have proved that the proposed algorithm decreases the execution time of current production lines at the TNG company.
Highlights
Scheduling is used to arrange the resources and tasks in many fields, where scheduling algorithms can have an important impact on the effectiveness and cost
In the wireless sensor networks, the node scheduling aims at selecting a set of nodes that provide the data service. is scheduling can effectively reduce the number of nodes and messages and at the same time extend the network lifetime [1,2,3]. e basic goal of Edge Computing [4] is finding the optimal scheduling for extending the Cloud’s resources such as servers and routers from remote data centers to the edge of the Cloud where they are closer to users, overcoming the bottlenecks issue by cloud computing and providing higher performance
Despite the importance of the Real-RCPSP, no one to the best of our knowledge has studied this problem. is paper is the first work that mentions Real-RCPSP; this section introduces the existing algorithms to solve another problem that is close to the Real-RCPSP, namely, MS-RCPSP
Summary
Scheduling is used to arrange the resources and tasks in many fields, where scheduling algorithms can have an important impact on the effectiveness and cost. Solving the MS-RCPSP [5,6,7] problem is to find out the schedule to execute the project in the shortest possible time without breaking any constraints. The scheduling algorithm’s goal is to find a schedule with the Journal of Advanced Transportation smallest execution time while meeting any task and resource constraints. Is paper presents a new problem, which is a more practical extension of the MSRCPSP, called the Real-RCPSP. In the Real-RCPSP, the processing time depends on the skill level of the resource. E section presents some previous algorithms for solving the ResourceConstrained Scheduling Problem.
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