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Extremely Fast Heuristic Event-Driven Job Shop Scheduler With a New Class of Extended Petri Nets

Extremely Fast Heuristic Event-Driven Job Shop Scheduler With a New Class of Extended Petri Nets
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Author(s): Alexander Kostin (Girne American University, Cyprus)
Copyright: 2021
Pages: 28
Source title: Handbook of Research on Applied AI for International Business and Marketing Applications
Source Author(s)/Editor(s): Bryan Christiansen (Global Training Group, Ltd, UK)and Tihana Škrinjarić (University of Zagreb, Croatia)
DOI: 10.4018/978-1-7998-5077-9.ch025

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Abstract

A very fast scheduling system is proposed and experimentally investigated. The system consists of a job shop manager and dynamic models of machines. A schedule is created in the course of a close cooperation with models of the machines that generate driving events for the scheduler. The system is implemented with a new class of extended Petri nets and runs in the environment of the Petri-net tool WINSIM. The scheduler creates a schedule sequentially, without any form of enumerative search. To investigate the scheduler performance, a large number of experiments were conducted with the use of few strategies. Due to a unique mechanism of monitoring of triggering events in the Petri net, the developed scheduler runs at least hundreds of times faster than any known single-processor job shop scheduler.

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