Swarm and Evolutionary Computation, Journal Year: 2024, Volume and Issue: 90, P. 101681 - 101681
Published: Aug. 18, 2024
Language: Английский
Swarm and Evolutionary Computation, Journal Year: 2023, Volume and Issue: 79, P. 101320 - 101320
Published: April 24, 2023
Language: Английский
Citations
21
Journal of Manufacturing Systems, Journal Year: 2023, Volume and Issue: 71, P. 390 - 405
Published: Oct. 7, 2023
Language: Английский
Citations
16
Complex & Intelligent Systems, Journal Year: 2023, Volume and Issue: 9(5), P. 4805 - 4816
Published: Feb. 15, 2023
Abstract Distributed manufacturing is the mainstream model to accelerate production. However, heterogeneous production environment makes engineer hard find optimal scheduling. This work investigates energy-efficient distributed permutation flow scheduling problem with flexible machine speed (DHPFSP-FMS) minimizing makespan and energy consumption simultaneously. In DHPFSP-FMS, local search misleads population falling into optima which reduces convergence diversity. To solve this problem, a bi-roles co-evolutionary algorithm proposed contains following improvements: First, global divided two swarms producer consumer balance computation. Second, three heuristic rules are designed get high-quality initialization population. Next, five problem-based strategies converging. Then, an efficient energy-saving strategy presented save energy. Finally, verify performance of algorithm, 22 instances generated based on Taillard benchmark, number numerical experiments adopted. The experiment results state that our superior state-of-arts more for DHPFSP-FMS.
Language: Английский
Citations
15
Engineering Applications of Artificial Intelligence, Journal Year: 2023, Volume and Issue: 120, P. 105921 - 105921
Published: Jan. 30, 2023
Language: Английский
Citations
14
Expert Systems with Applications, Journal Year: 2024, Volume and Issue: 248, P. 123278 - 123278
Published: Jan. 18, 2024
Language: Английский
Citations
6
Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)
Published: Jan. 29, 2024
Abstract This study investigates the no-wait flow shop scheduling problem and proposes a hybrid (HES-IG) algorithm that utilizes makespan as objective function. To address complexity of this NP-hard problem, HES-IG combines evolution strategies (ES) iterated greedy (IG) algorithm, hybridizing algorithms helps different mitigate their weaknesses leverage respective strengths. The ES begins with random initial solution uses an insertion mutation to optimize solution. Reproduction is carried out using (1 + 5)-ES, generating five offspring from one parent randomly. selection process employs (µ λ)-ES, allowing excellent solutions survive multiple generations until better surpasses them. IG algorithm’s straightforward search mechanism aids in further improving avoiding local minima. destruction operator randomly removes d-jobs, which are then inserted by construction operator. single approach, while acceptance–rejection criteria based on constant temperature. Parameters both calibrated Multifactor analysis variance technique. performance other Wilcoxon signed test. tested 21 Nos. Reeves 30 Taillard benchmark problems. has found 15 lower bound values for Similarly, Computational results indicate outperforms available techniques literature all sizes.
Language: Английский
Citations
5
Engineering Optimization, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 23
Published: April 12, 2024
With the complexity involved in manufacturing products, many companies use multiple processes to complete product processing. Most studies have been concerned with single production but neglected widespread joint flowshop scheduling problem (JFSP). In this article, a cooperative grey wolf optimizer (CGWO) is developed solve JFSP. First, according features of JFSP, corresponding mathematical model constructed, and three collaborative strategies random generation are proposed initialize population. process searching for prey, discretized search prey update mechanism proposed, which conducive balancing exploration exploitation. An energy-saving strategy decrease energy consumption. Moreover, four local mechanisms different optimization objectives enhance performance method attacking prey. The results show that CGWO effective solving
Language: Английский
Citations
5
Complex System Modeling and Simulation, Journal Year: 2023, Volume and Issue: 3(4), P. 282 - 306
Published: Dec. 1, 2023
The distributed hybrid flow shop scheduling problem (DHFSP), which integrates manufacturing models with parallel machines, has gained significant attention. However, in actual scheduling, some adjacent machines do not have buffers between them, resulting blocking. This paper focuses on addressing the DHFSP blocking constraints (DBHFSP) based production conditions. To solve DBHFSP, we construct a mixed integer linear programming (MILP) model for DBHFSP and validate its correctness using Gurobi solver. Then, an advanced iterated greedy (AIG) algorithm is designed to minimize makespan, modify Nawaz, Enscore, Ham (NEH) heuristic constraints. balance global local search capabilities of AIG, two effective inter-factory neighborhood strategies swap-based strategy are designed. Additionally, each factory mutually independent, movement within one does affect others. In view this, specifically memory-based decoding method insertion operations reduce computation time objective. Finally, shaking incorporated into mitigate premature convergence. Five algorithms used conduct comparative experiments AIG 80 test instances, experimental results illustrate that makespan relative percentage increase (RPI) obtained by 1.0% 86.1% respectively, better than algorithms.
Language: Английский
Citations
13
Expert Systems with Applications, Journal Year: 2023, Volume and Issue: 238, P. 121856 - 121856
Published: Sept. 26, 2023
Language: Английский
Citations
11
Computers & Industrial Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 110949 - 110949
Published: Feb. 1, 2025
Language: Английский
Citations
0