An extended flexible job shop scheduling problem with parallel operations

Lunardi, Willian T.; Voos, Holger

doi:10.1145/3243064.3243068

Cited by 15 publications

(5 citation statements)

References 17 publications

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“…The FA parameters is 75 fireflies, 500 generations, 1.0 attractiveness, and 0.35 randomization rate. For more details about of the GA and FA check [18].…”

Section: Numerical Resultsmentioning

confidence: 99%

An Imperialist Competitive Algorithm for a Real-World Flexible Job Shop Scheduling Problem

Lunardi

Voos

Cherri

2018

2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA)

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Traditional planning and scheduling techniques still hold important roles in modern smart scheduling systems. Realistic features present in modern manufacturing systems need to be incorporated into these techniques. The real-world problem addressed here is an extension of flexible job shop scheduling problem and is issued from the modern printing and boarding industry. The precedence between operations of each job is given by an arbitrary directed acyclic graph rather than a linear order. In this paper, we extend the traditional FJSP solutions representation to address the parallel operations. We propose an imperialist competitive algorithm for the problem. Several instances are used for the experiments and the results show that, for the considered instances, the proposed algorithm is faster and found better or equal solutions compared to the state-of-the-art algorithms.

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“…The FA parameters is 75 fireflies, 500 generations, 1.0 attractiveness, and 0.35 randomization rate. For more details about of the GA and FA check [18].…”

Section: Numerical Resultsmentioning

confidence: 99%

An Imperialist Competitive Algorithm for a Real-World Flexible Job Shop Scheduling Problem

Lunardi

Voos

Cherri

2018

2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA)

Self Cite

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“…Similar results are observed for the EA and it is worth mentioning that all ten runs per instance converged to the optimal solution. Tables 7 and 8 compare the results obtained from the EA considering different time limits (i.e., 50, 200, and 3600 seconds), the proposed MIP model considering a time limit of 3600 seconds, the exact MIP approach of Birgin et al (2013) and the metaheuristic Firefly Algorithm (FA) of Lunardi and Voos (2018) for the FJSSP with arbitrary precedence graphs. The proven optimal solutions are marked with the (*) symbol, while bold face is used to indicate the best upper bounds.…”

Section: Comparisons To the State Of The Art For The Fjssp With Arbit...mentioning

confidence: 99%

“…The authors present a mixed integer programming (MIP) model for the eFJSSP together with a set of benchmark problem instances. More recently, Lunardi and Voos (2018) developed a discrete firefly algorithm for the eFJSSP and Yu et al (2017) extended the mathematical formulation of Birgin et al (2013) to include job priorities and sequence flexibility.…”

Section: Introductionmentioning

confidence: 99%

Flexible Job Shop Scheduling Problems with Arbitrary Precedence Graphs

Kasapidis

Paraskevopoulos

Repoussis

et al. 2021

Production and Operations Management

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A common assumption in the shop scheduling literature is that the processing order of the operations of each job is sequential; however, in practice, there can be multiple connections and finish-to-start dependencies among the operations of each job. This paper studies flexible job shop scheduling problems with arbitrary precedence graphs. Rigorous mixed integer and constraint programming models are presented, as well as an evolutionary algorithm is proposed to solve large-scale problems. The proposed heuristic solution framework is equipped with efficient evolution and local search mechanisms as well as new feasibility detection and makespan estimation methods. To that end, new theorems are derived that extend previous theoretical contributions of the literature. Computational experiments on existing benchmark datasets show that the proposed solution methods outperform the current state-of-the-art. Overall, 59 new best solutions and 61 new lower bounds are produced for a total of 228 benchmark problem instances of the literature. To explore the impact of the arbitrary precedence graphs, lower bounds and heuristic solutions are generated for new large-scale problems. These experiments illustrate that the machine assignment flexibility and density of the precedence graphs, affect not only the makespan, but also the difficulty of producing good upper bounds.

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“…where an exclusive OR operations is employed to decide the hamming distance (Lunardi 2018 Basedonthedesignsdescribedabove,theoverallalgorithmisillustratedasAlgorithm1.…”

Section: Discrete Firefly Algorithm For Multi-workflow Schedulingmentioning

confidence: 99%

A Novel Approach to Location-Aware Scheduling of Workflows Over Edge Computing Resources

Yin

Zeng³

2020

International Journal of Web Services Research

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Edge computing is pushing the frontier of computing applications, data, and services away from centralized nodes to the logical extremes of a network. A major technological challenge for workflow scheduling in the edge computing environment is cost reduction with service-level-agreement (SLA) constraints in terms of performance and quality-of-service requirements because real-world workflow applications are constantly subject to negative impacts (e.g., network congestions, unexpected long message delays, shrinking coverage, range of edge servers due to battery depletion. To address the above concern, we propose a novel approach to location-aware and proximity-constrained multi-workflow scheduling with edge computing resources). The proposed approach is capable of minimizing monetary costs with user-required workflow completion deadlines. It employs an evolutionary algorithm (i.e., the discrete firefly algorithm) for the generation of near-optimal scheduling decisions. For the validation purpose, the authors show that our proposed approach outperforms traditional peers in terms multiple metrics based on a real-world dataset of edge resource locations and multiple well-known scientific workflow templates.

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An extended flexible job shop scheduling problem with parallel operations

Cited by 15 publications

References 17 publications

An Imperialist Competitive Algorithm for a Real-World Flexible Job Shop Scheduling Problem

An Imperialist Competitive Algorithm for a Real-World Flexible Job Shop Scheduling Problem

Flexible Job Shop Scheduling Problems with Arbitrary Precedence Graphs

A Novel Approach to Location-Aware Scheduling of Workflows Over Edge Computing Resources

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