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9 results on '"Sadollah, Ali"'

5. A review of energy-efficient scheduling in intelligent production systems

Author

Gao, Kaizhou, Huang, Yun, Sadollah, Ali, and Wang, Ling

Abstract

Recently, many manufacturing enterprises pay closer attention to energy efficiency due to increasing energy cost and environmental awareness. Energy-efficient scheduling of production systems is an effective way to improve energy efficiency and to reduce energy cost. During the past 10 years, a large amount of literature has been published about energy-efficient scheduling, in which more than 50% employed swarm intelligence and evolutionary algorithms to solve the complex scheduling problems. This paper aims to provide a comprehensive literature review of production scheduling for intelligent manufacturing systems with the energy-related constraints and objectives. The main goals are to summarize, analyze, discuss, and synthesize the existing achievements, current research status, and ongoing studies, and to give useful insight into future research, especially intelligent strategies for solving the energy-efficient scheduling problems. The scope of this review is focused on the journal publications of the Web of Science database. The energy efficiency-related publications are classified and analyzed according to five criteria. Then, the research trends of energy efficiency are discussed. Finally, some directions are pointed out for future studies.

Published
2024
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7. Size optimization of planar truss systems using the modified salp swarm algorithm.

Author

Altay, Onur, Cetindemir, Oguzhan, and Aydogdu, Ibrahim

Subjects
ALGORITHMS, MATHEMATICAL optimization, JOB performance, SWARM intelligence, STRUCTURAL optimization
Abstract

This work evaluates the performance of the salp swarm algorithm (SSA) for truss system optimization problems and presents a novel method called the modified salp swarm algorithm (MSSA). Five truss structures, previously optimized by metaheuristics and containing discrete and continuous variables, were used for the evaluations. Size and size–shape optimization types were considered. Although the SSA performs poorly and has convergence issues in initial random solutions, it reaches comparable solutions to previously published results, particularly in continuous problems. In contrast, the MSSA achieves the best solutions for discrete problems and is relatively close to the best results in the reference literature on continuous problems. Moreover, the MSSA convergence curves exhibit a modest increase in convergence rates, especially for discrete problems. It is envisaged that the findings will contribute to improving solution performance, convergence speed and security for future real-world applications. [ABSTRACT FROM AUTHOR]

Published
2024
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