A heuristic algorithm to minimize energy cost for scheduling test facilities

Sundaram, R. Meenakshi; Blair, L.M.

doi:10.1016/0360-8352(96)00151-9

Cited by 3 publications

(1 citation statement)

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“…Sundaram et al [1] developed a heuristic scheduling strategy for test facilities to minimize total operating costs, including power costs, labor costs and costs associated with the productivity decrease of night time operators. Test scheduling problem is similar to the job shop scheduling problem, which is known to be NP-complete and the use of heuristics is therefore justified.…”

Section: Related Workmentioning

confidence: 99%

Scheduling of Sea Test Based on Hybrid Ga

Chen

2006

2006 International Conference on Machine Learning and Cybernetics

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Involved with many test platforms, engineers, measurement instruments for a long time, the expenditure of a comprehensive sea test is tremendous. Therefore, a scheduling algorithm for sea test is proposed based on hybrid genetic algorithm. Considering resource requirement and resource available, queuing theory is applied for the concurrent arrangement of test procedures after the genetic algorithm finds a permutation candidate for voyage tests, which can guarantee that each solution candidate is feasible from the perspective of resource constraint. Simulation results show that the algorithm is effective and valid, which significantly reduces test duration.

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Section: Related Workmentioning

confidence: 99%

Scheduling of Sea Test Based on Hybrid Ga

Chen

2006

2006 International Conference on Machine Learning and Cybernetics

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An Efficient Heuristic to Optimize the Cost of Scheduling Production Tasks on Non-identical Parallel Production Lines

Ait Ben Hamou,

Jarir,

Elfirdoussi

et al. 2024

Lecture Notes in Networks and Systems

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Efficient Energy Use in Manufacturing Systems—Modeling, Assessment, and Management Strategy

Xia

Yang

et al. 2023

Energies

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Currently, studies on the energy efficiency of manufacturing systems usually lack synthetic and systematic techniques. In this paper, a holistic framework is demonstrated in order to achieve more sustainable manufacturing, which covers machine-level, system-level and life-cycle-level energy efficiency techniques. Based on these, the mechanism of how energy consumption is affected by machining processes and system operation is analyzed to achieve a comprehensive decision on energy efficiency optimization. Four main topics are included in this paper: (1) Hierarchical sustainability goals and metrics for energy-efficient manufacturing; (2) Machine-level machining processes optimization for energy efficiency enhancement; (3) System-level innovations for efficient consumption management; (4) Life-cycle level energy flow modeling and energy recycling strategy. An automotive engine manufacturing system is taken as an example to build a concrete understanding of the application of the framework. Moreover, this holistic framework establishes the theoretical basis for promoting the energy efficiency of automotive engine manufacturing systems. Furthermore, the proposed techniques can provide decision-making support for achieving sustainable manufacturing in a wider scope of mechanical manufacturing.

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A heuristic algorithm to minimize energy cost for scheduling test facilities

Cited by 3 publications

References 1 publication

Scheduling of Sea Test Based on Hybrid Ga

Scheduling of Sea Test Based on Hybrid Ga

An Efficient Heuristic to Optimize the Cost of Scheduling Production Tasks on Non-identical Parallel Production Lines

Efficient Energy Use in Manufacturing Systems—Modeling, Assessment, and Management Strategy

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