Article
Chemistry, Multidisciplinary
Jun-Hee Han, Ju-Yong Lee
Summary: This study focuses on optimizing a two-stage assembly-type flow shop with limited waiting time constraints to minimize the makespan. A mixed-integer programming formulation and various heuristic algorithms were proposed to tackle this NP-hard problem. Computational experiments showed the effectiveness of the iterated greedy algorithm and simulated annealing algorithm on different problem sizes.
APPLIED SCIENCES-BASEL
(2021)
Article
Computer Science, Interdisciplinary Applications
Ronghua Chen, Bo Yang, Shi Li, Shilong Wang, Qingqing Cheng
Summary: This study proposes an adaptive multi-objective Multi-population Grey Wolf Optimizer (AMPGWO) for solving the Flow Shop Scheduling Problem with Multi-machine Collaboration (FSSP-MC). The algorithm adjusts the quantity of individuals in each subpopulation using reinforcement learning to enhance population diversity, and shows good performance in solving large-scale problems.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Computer Science, Software Engineering
Shuilin Chen, Jianguo Zheng
Summary: This paper proposes a hybrid grey wolf optimizer (HGWO) to solve the permutation flow shop scheduling problem. The proposed algorithm improves the accuracy and efficiency by introducing cooperative initialization strategy, levy flight strategy, crossover and mutation strategy, and critical block exchange strategy.
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
(2023)
Article
Engineering, Industrial
Jose Renathoda de Silva Santana, Helio Yochihiro Fuchigami
Summary: This study proposes four mixed integer linear programming (MILP) models to solve the assembly flow shop problem, aiming at minimizing the makespan. The production environment consists of two stages, production and assembly, with the first stage having different machines for manufacturing parts and the second stage for final assembly. The performance measure considered is crucial for industries from various sectors, as it focuses on optimizing production time usage. Statistical analysis using different tools evaluated the performance and efficiency of the mathematical models, with emphasis on performance profiles analysis. Results showed that the mathematical models are efficient, with the position-based model demonstrating the best results for both small and large instances during computational experimentation. All the mathematical models can serve as direct decision-making tools for the production sequencing problem in the studied environment.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Zhenwei Zhu, Xionghui Zhou, Diansong Cao, Ming Li
Summary: Flexible job shop scheduling is crucial for customized products and small batch production. This study proposes a novel approach to solve the problem with job precedence constraints and demonstrates its effectiveness through extensive experiments.
APPLIED SOFT COMPUTING
(2022)
Article
Engineering, Industrial
Minh Hung Ho, Faicel Hnaien, Frederic Dugardin
Summary: This paper aims to build an energy-cost-aware scheduling plan for two-machine flow shop scheduling, tackling the joint optimization of makespan and electricity cost. The study shows the contribution of generating several optimal equivalent solutions with different electricity costs but the same makespan. The proposed approach significantly improves electricity cost under optimal makespan, providing good solutions for managers and decision makers to achieve energy cost savings without sacrificing productivity.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2021)
Article
Management
Alexander J. Benavides, Antony Vera
Summary: The NEH constructive heuristic and the iterated greedy algorithm are the best performing approximate methods for the permutational flow shop scheduling problem. Inserting jobs based on the resulting makespan evaluation and selecting the shortest makespan insertion positions, new tiebreakers have been proposed to improve the results and outperformed previous tiebreakers in experiments. The proposed tiebreakers, based on weighted and unweighted idle time increment approximations, embedded in the iterated greedy algorithm, prove to be the best approximate methods for the problem.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Computer Science, Information Systems
Sharif Naser Makhadmeh, Ammar Kamal Abasi, Mohammed Azmi Al-Betar, Mohammed A. Awadallah, Iyad Abu Doush, Zaid Abdi Alkareem Alyasseri, Osama Ahmad Alomari
Summary: This paper proposes a modified version of the Multi-objective Grey Wolf Optimizer for the Appliances Energy Scheduling Problem. The modified version combines the original searching mechanism with a novel neighbourhood selection strategy to improve local exploitation capabilities. Evaluation results show that the proposed method outperforms other comparison methods in almost all cases.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
(2022)
Article
Environmental Sciences
Huiping Wang, Yi Wang
Summary: Global warming caused by CO2 emissions has a direct impact on human health and quality of life. Accurate prediction of CO2 emissions is crucial for formulating scientific and reasonable low-carbon environmental policies. This paper proposes a new fractional grey Bernoulli model (FGBM(1,1,t(alpha))) for predicting CO2 emissions, which demonstrates high adaptability and accuracy compared to other models. The study also predicts the future trends of CO2 emissions in different regions over the next 5 years.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2022)
Article
Engineering, Multidisciplinary
XinYu Li, Jin Xie, QingJi Ma, Liang Gao, PeiGen Li
Summary: This paper proposes an effective improved gray wolf optimizer (IGWO) for solving the distributed flexible job shop scheduling problem (DFJSP). By designing new encoding and decoding schemes, developing crossover operators and local search strategies, the study successfully achieves improved solution quality and computational efficiency.
SCIENCE CHINA-TECHNOLOGICAL SCIENCES
(2022)
Article
Engineering, Mechanical
Hao-Chang Chen, Du-Qu Wei
Summary: This work proposes a chaos prediction model based on ESN optimized by SOGWO, which achieves better prediction performance and accurately predicts a much longer period of time by optimizing the input weight matrix and introducing an opposition strategy.
NONLINEAR DYNAMICS
(2021)
Article
Computer Science, Artificial Intelligence
Ming Li, Bin Su, Deming Lei
Summary: The paper considers the fuzzy distributed assembly flow shop scheduling problem and proposes an algorithm optimized through imperialist cooperation. Experimental results demonstrate the excellent performance of the algorithm in solving the problem.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2021)
Article
Computer Science, Interdisciplinary Applications
Cuiyu Wang, Li Zhao, Xinyu Li, Yang Li
Summary: This paper proposes a model and algorithm for the welding shop inverse scheduling problem (WSISP) and validates the effectiveness of the proposed method through experiments.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Computer Science, Artificial Intelligence
Bilal H. Abed-alguni, Noor Aldeen Alawad
Summary: This paper introduces a discrete version of the Distributed Grey Wolf Optimizer (DGWO) for scheduling dependent tasks in cloud computing environments. DGWO outperformed other optimization-based scheduling algorithms such as PSO and Grey Wolf Optimizer, providing faster task distribution to VMs and the best makespan in simulation results.
APPLIED SOFT COMPUTING
(2021)
Article
Computer Science, Interdisciplinary Applications
Hugo Hissashi Miyata, Marcelo Seido Nagano
Summary: This article introduces a distributed blocking flow shop scheduling problem with sequence-dependent setup times and maintenance operations, and proposes an iterative greedy method to solve this problem. Computational experiments demonstrate that the proposed method achieves a good balance between effectiveness and efficiency.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Engineering, Multidisciplinary
Vahid Kayvanfar, S. M. Moattar Husseini, B. Karimi, Mohsen S. Sajadieh
ENGINEERING OPTIMIZATION
(2018)
Article
Engineering, Manufacturing
Amin Aalaei, Vahid Kayvanfar, Hamid Davoudpour
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE
(2019)
Article
Computer Science, Interdisciplinary Applications
Nima Moradi, Vahid Kayvanfar, Majid Rafiee
Summary: The 0-1 knapsack problem is a classic problem with various applications, and this paper compares different SA-based algorithms to find the most efficient one. The proposed population-based SA algorithm (PSA) outperforms other SA-based solvers in terms of exploration and exploitation, making it a promising approach for future optimization algorithms in KP01.
ENGINEERING WITH COMPUTERS
(2022)
Article
Environmental Sciences
Pouria Khodabandeh, Vahid Kayvanfar, Majid Rafiee, Frank Werner
Summary: Management of home health care is a key concern for governments and decision-makers, with the study finding that upgrading costs can lead to significant hidden costs for companies.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
(2021)
Article
Management
Amin Zaheri, Majid Rafiee, Vahid Kayvanfar
Summary: This paper studies the impact of discounts on the relationships between a manufacturer and a retailer, comparing members' profits under cooperative and non-cooperative games. By modeling through different approaches, it analyzes members' profits and their inclination to change, providing a decision-making tool for maximizing profits.
JOURNAL OF MODELLING IN MANAGEMENT
(2021)
Article
Operations Research & Management Science
Elham Rastpour, Vahid Kayvanfar, Majid Rafiee
Summary: This research aims to determine the main criteria of green supply chain management and provide a framework for assessing and comparing the greenness of dairy industries. Through literature study and expert opinions, the framework is developed and evaluated using various methods. The findings from this research provide valuable insights for companies in terms of their greenness and functionality.
INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE AND ENGINEERING MANAGEMENT
(2022)
Article
Engineering, Industrial
Vahid Kayvanfar, M. Zandieh, Mehrdad Arashpour
Summary: This research investigates the economic lot scheduling problem and proposes a hybrid algorithm that outperforms other algorithms in terms of solution quality and diversity.
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE-OPERATIONS & LOGISTICS
(2022)
Article
Engineering, Multidisciplinary
Majid Rafiee, Vahid Kayvanfar, Atieh Mohammadi, Frank Werner
Summary: This paper investigates the operator assignment problem in cellular manufacturing systems, with a focus on operator learning and forgetting effects, as well as handling uncertain parameters. Numerical instances solving and statistical analysis of the model were conducted to gain managerial insights.
APPLIED MATHEMATICAL MODELLING
(2022)
Article
Economics
Farid Kochakkashani, Vahid Kayvanfar, Alireza Haji
Summary: This study aims to support pharmaceutical supply chain planning during the COVID-19 epidemic by providing a mathematical model. The model minimizes costs and maintains an acceptable service level. Clustering of pharmaceuticals and vaccines reduces problem size and solving time.
SOCIO-ECONOMIC PLANNING SCIENCES
(2023)
Article
Social Sciences, Interdisciplinary
Atefeh Naseri, Vahid Kayvanfar, Shaya Sheikh, Frank Werner
Summary: This research explores the impact of social media on the marketing goals of organizations in Iran during the COVID-19 pandemic. The results show a significant positive relationship between the use of social media and distraction level, and the gender of marketers has an impact on the perceived usefulness and application of social media. Additionally, working hours per day positively affect social media usage and marketing performance.
SOCIAL SCIENCES-BASEL
(2022)
Article
Mathematics, Applied
Pouria Khodabandeh, Vahid Kayvanfar, Majid Rafiee, Frank Werner
Summary: In this study, a new mathematical model is proposed to address the issue of flexibility in starting/ending places of nurses' routes when providing services at patients' homes. The efficiency of the proposed approach is confirmed through real-world problem solving, and sensitivity analyses on the required features of the services provide insights for management and future studies.
Review
Hospitality, Leisure, Sport & Tourism
Ramina Khorsand, Majid Rafiee, Vahid Kayvanfar
TOURISM MANAGEMENT PERSPECTIVES
(2020)
Article
Operations Research & Management Science
Shaya Sheikh, G. M. Komaki, Vahid Kayvanfar, Ehsan Teymourian
OPERATIONS RESEARCH PERSPECTIVES
(2019)
Article
Management
Vahid Kayvanfar, S. M. Moattar Husseini, Zhang NengSheng, Behrooz Karimi, Mohsen S. Sajadieh
MANAGEMENT RESEARCH REVIEW
(2019)
Proceedings Paper
Computer Science, Artificial Intelligence
Vahid Kayvanfar, Shaya Sheikh, G. M. Komaki
2018 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA)
(2018)