Article
Multidisciplinary Sciences
Kaifeng Geng, Li Liu, Zhanyong Wu
Summary: This study considers the distributed heterogeneous re-entrant hybrid flow shop scheduling problem with sequence dependent setup times, considering factory eligibility constraints under time of use price. It proposes a multi-objective Artificial Bee Colony Algorithm to optimize both the makespan and total energy consumption. The algorithm demonstrates its effectiveness in solving the scheduling problem through extensive experiments.
SCIENTIFIC REPORTS
(2022)
Article
Engineering, Industrial
Junhao Chen, Xiaoliang Jia, Qixuan He
Summary: This study proposes a novel bi-level multi-objective genetic algorithm to solve the integrated problem of assembly line balancing and part feeding. The algorithm outperforms traditional methods in terms of approximation and computational efficiency.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
Binghai Zhou, Zhe Zhao
Summary: This study focuses on the dynamic part feeding scheduling problem under a Kanban system in mixed-model assembly lines in the automobile industry. A hybrid fuzzy-neural-based dynamic scheduling method is proposed to optimize productivity and part feeding costs simultaneously. Computational experiments demonstrate the superiority of the method in dynamic manufacturing environments.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Thermodynamics
Juan Zou, Xu Yang, Zhongbing Liu, Jiangyang Liu, Ling Zhang, Jinhua Zheng
Summary: The algorithm uses a multi-objective bilevel optimization approach to solve complex energy hub system planning problems. It improves optimization speed through preference selection and trisection search, saving computational time and addressing the inability of commercial optimizers to solve nonlinear discrete problems.
Article
Computer Science, Interdisciplinary Applications
Stefan Bock, Nils Boysen
Summary: This study focuses on real-time launch control in mixed-model assembly lines, proposing an integrated solution and demonstrating its superiority over alternative launching approaches in a simulation study. The integrated approach not only improves production efficiency but also reduces safety stocks of parts within workstations.
COMPUTERS & OPERATIONS RESEARCH
(2021)
Article
Computer Science, Artificial Intelligence
Yatong Chang, Wenjian Luo, Xin Lin, Zhen Song, Carlos A. Coello Coello
Summary: This paper proposes the definition of the biparty multiobjective optimal power flow (BPMOOPF) problem and introduces a novel evolutionary biparty multiobjective optimization algorithm (BPMOOPF-EA) to solve the problem. Experimental results show that BPMOOPF-EA outperforms other algorithms in solving the MOOPF problem.
APPLIED SOFT COMPUTING
(2023)
Article
Computer Science, Artificial Intelligence
Binghai Zhou, Zhexin Zhu
Summary: The paper aims to construct an energy-saving scheduling scheme for part feeding tasks of mobile robots in automobile mixed model assembly lines. The MDRCI algorithm is developed to deal with the multi-objective problem, outperforming other benchmark algorithms in global search capability and search depth. Managerial insights on balancing inventory level and energy consumption contribute to practical greening scheduling processes.
NEURAL COMPUTING & APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Mehmet Altinoz, O. Tolga Altinoz
Summary: This research addresses a capacitated vehicle routing problem with urgency and contamination rate. It proposes using multiobjective optimization algorithms to optimize the time and infectiousness rate, two main issues in the problem.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Computer Science, Interdisciplinary Applications
Lue Tao, Yun Dong, Weihua Chen, Yang Yang, Lijie Su, Qingxin Guo, Gongshu Wang
Summary: This study addresses a new variant of the assembly line feeding problem in automobile manufacturing, proposing a novel mathematical model and algorithm that achieve superior cost savings, solution quality, and convergence efficiency while providing decision support for managers.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Computer Science, Artificial Intelligence
Chuang Liu, Wanghui Shen, Le Zhang, Hong Yang, Yingkui Du, Zhonghu Yuan, Hai Zhao
Summary: This paper proposes an improved membrane algorithm for solving multimodal multiobjective problems, which is based on the framework of P system. By introducing three elements from P system and verifying the effectiveness through simulation experiments, the proposed algorithm shows competitive advantage in solving the problems.
INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE
(2021)
Article
Computer Science, Information Systems
Mohammad H. Nadimi-Shahraki, Shokooh Taghian, Seyedali Mirjalili, Laith Abualigah, Mohamed Abd Elaziz, Diego Oliva
Summary: The optimal power flow is a crucial tool in optimizing control parameters of a power system, with the whale optimization algorithm being widely used for such problems. This paper proposes an enhanced whale optimization algorithm to improve exploration ability and achieve better solutions across diverse power system scales. The comparison of results demonstrates that the enhanced algorithm outperforms other comparative algorithms in solving both single- and multi-objective optimal power flow problems.
Article
Computer Science, Interdisciplinary Applications
Wenchong Chen, Humyun Fuad Rahman, Qing Zhou, Shuchun Liu, Hongwe Liu, Ershi Qi
Summary: This paper investigates a proactive in-house part-feeding (PIP) approach that integrates real-time data from shop floors with the physical properties of a mixed-model assembly system to enable real-time actions based on disruption-driven prediction. An event-driven proactive prediction for replenishments is implemented after coupling various data. An adaptive large neighbourhood search (ALNS) is developed to obtain the best solution for rerouting. A case study and computational results demonstrate the efficiency and satisfactory performance of the PIP and ALNS in reducing distribution costs.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Construction & Building Technology
Hosang Hyun, Inseok Yoon, Hyun-Soo Lee, Moonseo Park, Jeonghoon Lee
Summary: A flexible production duration is crucial due to the rising demand for modular construction, coupled with the benefits of reduced labor requirements. The multiobjective optimization model for modular unit production line (MOMUPL) uses genetic algorithms to address design and scheduling differences, offering various optimization results for project managers to choose from. Ultimately, MOMUPL is expected to decrease scheduling duration, project labor costs, and overall project duration.
AUTOMATION IN CONSTRUCTION
(2021)
Article
Chemistry, Multidisciplinary
Lingren Kong, Jianzhong Wang, Peng Zhao
Summary: Dynamic weapon target assignment (DWTA) is an effective method for solving the multi-stage battlefield fire optimization problem, with a meaningful and effective model established in this paper. The model includes conflicting objectives of maximizing combat benefits and minimizing weapon costs, as well as various constraints. An improved multiobjective particle swarm optimization algorithm (IMOPSO) is proposed to solve the complex DWTA problem, showing better convergence and distribution compared to other state-of-the-art algorithms in experimental results.
APPLIED SCIENCES-BASEL
(2021)
Article
Computer Science, Information Systems
Yajie Zhang, Ye Tian, Hao Jiang, Xingyi Zhang, Yaochu Jin
Summary: In recent years, solving constrained multiobjective optimization problems by introducing simple helper problems has become popular. This study provides a comprehensive overview of existing constrained multiobjective evolutionary algorithms and proposes a novel helper-problem-assisted CMOEA, which has shown competitive performance in experiments.
INFORMATION SCIENCES
(2023)
Article
Engineering, Industrial
Morteza Ghobakhloo, Masood Fathi
JOURNAL OF MANUFACTURING TECHNOLOGY MANAGEMENT
(2020)
Article
Computer Science, Interdisciplinary Applications
Masood Fathi, Amir Nourmohammadi, Amos H. C. Ng, Anna Syberfeldt, Hamidreza Eskandari
ENGINEERING COMPUTATIONS
(2020)
Article
Computer Science, Cybernetics
Milad Yousefi, Moslem Yousefi, Masood Fathi, Flavio S. Fogliatto
Article
Engineering, Industrial
Amir Nourmohammadi, Hamidreza Eskandari, Masood Fathi, Amos H. C. Ng
Summary: This study relaxes the assumption of using identical transport vehicles when deciding on the supermarkets' location and develops a mixed-integer programming (MIP) model for the integrated supermarket location and transport vehicles selection problems (SLTVSP). A hybrid genetic algorithm (GA) with variable neighborhood search (GA-VNS) is proposed to address large-sized problems, outperforming other algorithms and providing a good approximation of the MIP solutions. Analysis reveals the benefits of applying different transport vehicles for SLTVSP.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2021)
Article
Green & Sustainable Science & Technology
J. Rincon-Moreno, M. Ormazabal, M. J. Alvarez, C. Jaca
Summary: The study aims to address the lack of well-defined indicators for measuring circularity of products, companies, and regions in the context of the circular economy. By proposing a set of indicators adapted from existing ones, simplicity and effectiveness are guaranteed, closely based on indicators proposed by government bodies. The study demonstrates that the indicators used for assessing the circular economy at the macro level can also be applied at the micro level, showing applicability and consistency across different economic activities.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Green & Sustainable Science & Technology
Masood Fathi, Amir Nourmohammadi, Morteza Ghobakhloo, Milad Yousefi
Article
Green & Sustainable Science & Technology
John Rincon-Moreno, Marta Ormazabal, Maria J. Alvarez, Carmen Jaca
Article
Green & Sustainable Science & Technology
Masood Fathi, Morteza Ghobakhloo
Review
Green & Sustainable Science & Technology
Morteza Ghobakhloo, Masood Fathi, Mohammad Iranmanesh, Parisa Maroufkhani, Manuel E. Morales
Summary: This study conducted a systematic literature review to explore the concept, scope, definition, functionality, and sustainability implications of Industry 4.0. The findings suggest that Industry 4.0 transformation could address pressing issues in manufacturing-economic development and provide future research directions.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Management
Montserrat-Ana Miranda, Maria Jesus Alvarez, Cyril Briand, Matias Urenda Moris, Victoria Rodriguez
Summary: The study aims to reduce carbon emissions and costs in an automobile production plant by improving operational management efficiency of a serial assembly line with the assistance of an electric tow vehicle. The research uses mixed-integer linear programming and bi-objective optimization models to find the most eco-efficient assembly line strategy.
JOURNAL OF MODELLING IN MANAGEMENT
(2021)
Article
Computer Science, Information Systems
Enrique Ruiz Zuniga, Matias Urenda Moris, Anna Syberfeldt, Masood Fathi, Juan Carlos Rubio-Romero
Article
Health Policy & Services
M. A. Miranda, S. Salvatierra, I. Rodriguez, M. J. Alvarez, V. Rodriguez
HEALTH CARE MANAGEMENT SCIENCE
(2020)
Proceedings Paper
Automation & Control Systems
Amir Nourmohammadi, Masood Fathi, Amos H. C. Ng
52ND CIRP CONFERENCE ON MANUFACTURING SYSTEMS (CMS)
(2019)