Simulation-Based Scheduling and Planning Approach to Job-Shop Production System

In recent years, with the advent of Industry 4.0, the concepts of Cyber-Physical System and Internet of Things arise, allowing to shift from a classical hierarchical approach to the Manufacturing Planning and Control (MPC) system to a new class of more decentralized architecture.

This work aims to extend the decentralized scheduling and planning approach to a job-shop production system.

Due to the complexity of a Job-Shop Scheduling Problem, the researchers firstly introduce a parametric simulation model to represent a generic job-shop system. Then, the research team proposes a newly dispatching rule for the order admittance in a semi-heterarchical job-shop environment for the lowest machine level.

Production planning and scheduling simulation model

A multi-method approach based on Discrete Event Simulation (DES) and Multi-Agent Systems (MAS) was used to develop the simulation model, using the AnyLogic 8.5.2 as simulation software.

Production planning and scheduling model logic

Logic of the main model

In the production planning and scheduling model, two populations of agents are represented as resources and jobs. Resources represent the entities responsible for processing the product (e.g. machines). Jobs are the objects that undergo machining to become, at the end of the technological cycle, finished products. Each job agent contains two additional populations, essential for the work of the Job Shop system: operations and transitions.

The Job agents receive the call, process the reply, and return their availability. The job answer consists of a proposal represented by a Proposal agent.

The Resource agent receives the Proposals from the Jobs and keeps them in a different proposal’s population inside the Resource agent. When all the proposal has been collected, the Resource switches from the “Wait reply” state to the “Evaluation Proposal and Acceptance” state.

The resources, during the “Evaluation and Acceptance” phase, assign a score to each proposal, choosing the one with the highest score. Here is where the dynamic Dispatching Rule (DRP) takes place, for the score evaluation of the jobs in an Industry 4.0 semi-heterarchical job-shop scenario.


This work proposed the first decentralized scheduling and planning approach for a job-shop production system. Due to the complexity of such a scenario, a parametric simulation model that allows representation of many job-shop production systems was introduced.

The analysis of results showed a significant productivity increase in all the considered production planning and scheduling scenarios with the use of the proposed dispatching rule – DRP.

This production planning and scheduling project may be considered as a first step towards the development of a different approach to the scheduling problem for the job-shop production system.

Production planning and scheduling model: agent statechart

Job agent statechart diagram

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