Modeling and algorithm for resource-constrained multi-project scheduling problem based on detection and rework
ISSN: 0144-5154
Article publication date: 29 January 2021
Issue publication date: 27 July 2021
Abstract
Purpose
To meet the requirement of establishing an effective schedule for the assembly process with overall detection and rework, this paper aims to address a new problem named resource-constrained multi-project scheduling problem based on detection and rework (RCMPSP-DR).
Design/methodology/approach
First, to satisfy both online and offline scheduling, a mixed integer programming model is established with a weighted bi-objective minimizing the expected makespan and the solution robustness. Second, an algorithm that combines a tabu search framework with a critical chain-based baseline generation scheme is designed. The tabu search framework focuses on searching for a reasonable resource flow representing the execution sequence of activities, while the critical chain-based baseline generation scheme establishes a buffered baseline schedule by estimating the tradeoff between two aspects of bi-objective.
Findings
The proposed algorithm can get solutions with gaps from −4.45% to 2.33% when compared with those obtained by the commercial MIP solver CPLEX. Moreover, the algorithm outperforms four other algorithms in terms of both objective performance and stability over instances with different weighting parameters, which reveals its effectiveness.
Originality/value
The represented RCMPSP-DR considering the overall detection and rework is an extension of the scheduling problem for large-scale equipment. An effective algorithm is proposed to establish the baseline schedule and determine the execution sequence of activities for the assembly process, which is significant for practical engineering applications.
Keywords
Citation
Zhu, H., Lu, Z., Lu, C. and Ren, Y. (2021), "Modeling and algorithm for resource-constrained multi-project scheduling problem based on detection and rework", Assembly Automation, Vol. 41 No. 2, pp. 174-186. https://doi.org/10.1108/AA-09-2020-0132
Publisher
:Emerald Publishing Limited
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