Multiresource-Constrained Flexible Job Shop Scheduling With Fixture Pallets and Setup Stations Under Pallet Automation Systems

Read full text
Authors: Yulu Zhou, Jun Lv, ShiChang DU, X. Y. Shen, Molin Liu
Cited by: 68
References: 51

Abstract

Pallet automation systems (PASs) are critical in flexible manufacturing for their ability to integrate diverse production resources, such as machines, fixture pallets (FPs), and setup stations (STs). In traditional flexible manufacturing systems (FMSs), loading/unloading typically occurs at machines, limiting the machines’ capacity. To address this, in PASs, workpieces are loaded and unloaded from the machines at a limited number of STs, so loading, processing, and unloading are three separate segments. However, the research on PASs is limited, and existing studies mainly focused on machines while overlooking FPs and STs. A critical challenge is the tight coupling between resource selection and operation sequencing. To address this gap, we investigate a multiresource-constrained flexible job shop scheduling problem (MRFJSP) with FPs and STs under PASs (MRFFS). First, a mixed-integer programming model is proposed to minimize makespan. Second, a four-layer encoding scheme and a new decoding method with time period insertion based on the intersection of available time of multiple resources (TPI-IARs) are presented to obtain feasible schedule solutions and shrink the search space. Third, a new search algorithm based on critical paths and points mutation (SACP) is developed to effectively balance exploration and exploitation. Finally, four case studies are designed to demonstrate the validity and effectiveness of this work.

Fields of Study & Subjects

Scheduling and Optimization Algorithms Flexible and Reconfigurable Manufacturing Systems Advanced Manufacturing and Logistics Optimization

Publication details

Journal / source
IEEE Transactions on Systems Man and Cybernetics Systems
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Volume
56
Issue
4
Pages
2868–2881
Publication date
28 January 2026