Execution of revised BMIM similarity coefficient for part family formation in reconfigurable manufacturing system DOI
Gaurav Kumar, Kapil Kumar Goyal, Neera Batra

et al.

Journal of Adhesion Science and Technology, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 23

Published: Oct. 9, 2024

The reconfigurable manufacturing system (RMS) is an advanced strategy that enables precise adjustment of functionality and capacity to meet fluctuating demands economically. RMS focuses on part families, allowing configurations be adapted for new requirements. Optimizing flow line design produce various parts involves minimizing reconfigurations associated costs by enhancing operation sequence similarity. This article proposes a novel optimization using the Longest Common Subsequence (LCS) method reduce bypassing moves machine idle times. study introduces similarity coefficient derived from LCS employs average linkage hierarchical clustering categorize in case study. Unlike traditional methods, this approach considers material movements both before initial after final processing station, addressing gaps move calculations. impact different weighting scenarios Type-II (ω) idleness (β) was examined. For example, with weights {1.0, 0.6, 0.3, 0.0} equal weightings (α) set at 0.5, threshold value 0.3 results eight clusters, such as Cluster 1 {1, 11, 10, 12} 3 {3, 5, 6, 4, 15, 9, 13, 14, 7, 8}. Lower values lead fewer clusters larger sizes, indicating more consolidated family grouping. Various handling demonstrate how affect sizes. enhances efficiency integrating comprehensive considerations optimizing based operational similarities.

Language: Английский

A Q-learning-based multi-population algorithm for multi-objective distributed heterogeneous assembly no-idle flowshop scheduling with batch delivery DOI
Zikai Zhang, Qiuhua Tang, Liping Zhang

et al.

Expert Systems with Applications, Journal Year: 2024, Volume and Issue: 263, P. 125690 - 125690

Published: Nov. 12, 2024

Language: Английский

Citations

3

Optimized Grid Partitioning and Scheduling in Multi-Energy Systems Using a Hybrid Decision-Making Approach DOI Creative Commons
Peng Liu, Tieyan Zhang,

Furui Tian

et al.

Energies, Journal Year: 2024, Volume and Issue: 17(13), P. 3253 - 3253

Published: July 2, 2024

This paper presents a thorough review of our state-of-the-art technique for enhancing dynamic grid partitioning and scheduling in multi-energy source systems. We use hybrid approach to T-spherical fuzzy sets, combining the alternative ranking order method accounting two-step normalization (AROMAN) alternating enable normalisation with based on removal effects criteria (MEREC) eliminating effects. enables us obtain highest level accuracy from findings. To ascertain relative importance these criteria, we MEREC perform rigorous examination influence that each evaluation criterion has outcomes decision-making process. In addition, AROMAN provide strong foundation assessing potential solutions by spherical sets account any ambiguity. illustrate how successfully considers several factors, such as social acceptability, technical feasibility, environmental sustainability, economic through analysis an extensive case study. Our provides decision-makers (DMs) rational framework choosing best division options. is done effort support administration design resilient sustainable research contributes growing body knowledge this area offering insights help direct policy, planning, investment decisions shift towards more energy infrastructures. Moreover, it adds information multi-criteria (MCDM) system optimization.

Language: Английский

Citations

2

Optimized Dynamic Service Placement for Enhanced Scheduling in Fog-Edge Computing Environments DOI

Yongxing Lin,

Yan Shi,

Nazila Mohammadnezhad

et al.

Sustainable Computing Informatics and Systems, Journal Year: 2024, Volume and Issue: 44, P. 101037 - 101037

Published: Sept. 11, 2024

Language: Английский

Citations

2

Deep reinforcement learning assisted novelty search in Voronoi regions for constrained multi-objective optimization DOI
Yufei Yang, Changsheng Zhang, Yi Liu

et al.

Swarm and Evolutionary Computation, Journal Year: 2024, Volume and Issue: 91, P. 101732 - 101732

Published: Sept. 24, 2024

Language: Английский

Citations

2

A hybrid evolutionary algorithm to improve task scheduling and load balancing in fog computing DOI
Dongxian Yu,

Weiyong Zheng

Cluster Computing, Journal Year: 2024, Volume and Issue: 28(1)

Published: Nov. 20, 2024

Language: Английский

Citations

2

Analysis of Transient Stability through a Novel Algorithm with Optimization under Contingency Conditions DOI Creative Commons
Kumar Reddy Cheepati, Suresh Babu Daram, Ch. Rami Reddy

et al.

Energies, Journal Year: 2024, Volume and Issue: 17(17), P. 4404 - 4404

Published: Sept. 3, 2024

Predicting the need for modeling and solutions is one of largest difficulties in electricity system. The static-constrained solution, which not always powerful, provided by Gradient Method Power Flow (GMPF). Another benefit using both dynamic transient restrictions that GMPF will increase stability against faults. system observed under contingency situations Dynamic Stability Constrained (DSCGMPF). population optimization technique foundation a recent algorithm called Training Learning Based Optimization (TLBO). TLBO-based approach obtaining DSCGMPF implemented this work. total losses cost individual generators have been optimized. Analysis limits conditions has conducted as well. To illustrate suggested approaches, Standard 3 machine 5-bus simulated MATLAB 2022B platform.

Language: Английский

Citations

1

A novel advanced hybrid fuzzy MPPT controllers for renewable energy systems DOI Creative Commons

Shaik Rafi Kiran,

Faisal Alsaif

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Sept. 10, 2024

Language: Английский

Citations

1

Location-aware job scheduling for IoT systems using cloud and fog DOI Creative Commons
Xiaomo Yu,

Mingjun Zhu,

Ming Zhu

et al.

Alexandria Engineering Journal, Journal Year: 2024, Volume and Issue: 110, P. 346 - 362

Published: Oct. 11, 2024

Language: Английский

Citations

1

An advanced RIME Optimizer with Random Reselection and Powell Mechanism for Engineering Design DOI Creative Commons

Shiqi Xu,

Wei Jiang, Yi Chen

et al.

Journal of Computational Design and Engineering, Journal Year: 2024, Volume and Issue: 11(6), P. 139 - 179

Published: Oct. 18, 2024

Abstract RIME is a recently introduced optimization algorithm that draws inspiration from natural phenomena. However, has certain limitations. For example, it prone to falling into Local Optima, thus failing find the Global and problem of slow convergence. To solve these problems, this paper introduces an improved (PCRIME), which combines random reselection strategy Powell mechanism. The enhances population diversity helps escape while mechanism improve convergence accuracy optimal solution. verify superior performance PCRIME, we conducted series experiments at CEC 2017 2022, including qualitative analysis, ablation studies, parameter sensitivity comparison with various advanced algorithms. We used Wilcoxon signed-rank test Friedman confirm advantage PCRIME over its peers. experimental data show ability robustness. Finally, applies five real engineering problems proposes feasible solutions comprehensive index definitions for prove stability proposed algorithm. results can not only effectively practical but also excellent stability, making

Language: Английский

Citations

1

Proximal Policy Optimization with Population-based Variable Neighborhood Search Algorithm for Coordinating Photo-Etching and Acid-Etching Processes in Sustainable Storage Chip Manufacturing DOI
Weijian Zhang, Min Kong, Yajing Zhang

et al.

Journal of Industrial Information Integration, Journal Year: 2024, Volume and Issue: 42, P. 100727 - 100727

Published: Nov. 1, 2024

Language: Английский

Citations

1