Article
Automation & Control Systems
Jiang-Ping Huang, Quan-Ke Pan, Zhong-Hua Miao, Liang Gao
Summary: The study focuses on the DPFSP problem with SDST, proposing three constructive heuristics and a DABC algorithm. The heuristics are based on greedy rule and local search, while the DABC algorithm balances local and global exploration with six composite neighborhood operators. A problem-oriented local search method is introduced to improve the best individual in the population. The proposed methods are shown to be effective compared to existing algorithms in solving the problem.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2021)
Article
Engineering, Industrial
Hugo Hissashi Miyata, Marcelo Seido Nagano
Summary: Nowadays, distributed scheduling problem is a reality in many companies. Over the last years, an increasingly attention has been given to the distributed flow shop scheduling problem and the addition of constraints to the problem. This article introduces a new distributed no-wait flow shop scheduling problem using a mix of mixed-integer linear programming and heuristic algorithms. Studies show that the proposed algorithm performs well in the trade-off between efficiency and effectiveness.
JOURNAL OF MANUFACTURING SYSTEMS
(2021)
Article
Engineering, Industrial
Hugo Hissashi Miyata, Marcelo Seido Nagano, Jatinder N. D. Gupta
Summary: This article incorporates maintenance operations into the blocking flow shop to minimize total completion time and maintenance costs. It develops a mixed integer linear programming and procedures for job sequence with maintenance. The study adapts different algorithms to solve small, medium, and large sets of instances, and evaluates their performance based on trade-off between solution quality and computational time.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
Weishi Shao, Zhongshi Shao, Dechang Pi
Summary: This paper investigates a distributed no-wait flexible flow shop scheduling problem with makespan criterion, presenting a mixed-integer linear programming model and machine selection method, as well as developing greedy factory assignment rules and dispatch rules. Multiple constructive heuristics are obtained by combining different rules, and a variable neighborhood descend constructive heuristic version is designed to tackle the problem.
COMPUTERS & OPERATIONS RESEARCH
(2021)
Article
Automation & Control Systems
Bin Qian, Zi-Qi Zhang, Rong Hu, Huai-Ping Jin, Jian-Bo Yang
Summary: In this article, a matrix-cube-based estimation of distribution algorithm is proposed to solve the no-wait flow-shop scheduling problem with sequence-dependent setup times and release times. The algorithm demonstrates efficient exploration and exploitation in the solution space, leading to improved solutions compared to state-of-the-art algorithms.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
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
Computer Science, Artificial Intelligence
Michael Mario Wocker, Frederik Ferid Ostermeier, Tobias Wanninger, Ronny Zwinkau, Jochen Deuse
Summary: In highly automated manufacturing systems, preventive maintenance activities need to be executed during production times, even in 24/7 operation. This research introduces a mixed-integer program that models both job scheduling and maintenance activity assignment in flexible job shops. A local search algorithm is developed to solve both problems in an integrated way. Numerical studies based on real data show that joint job scheduling and maintenance activity assignment is essential for minimizing the makespan and only a limited amount of maintenance activities can be compensated.
JOURNAL OF INTELLIGENT MANUFACTURING
(2023)
Article
Computer Science, Artificial Intelligence
Carla Talens, Victor Fernandez-Viagas, Paz Perez-Gonzalez, Antonio Costa
Summary: This paper addresses the 2-stage assembly scheduling problem aiming to minimize makespan with availability constraints. Novel constructive and composite heuristics are proposed, which outperform existing methods in computational evaluations.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Management
Masoumeh Ghorbanzadeh, Mohammad Ranjbar
Summary: This paper investigates an energy-aware flow shop scheduling problem with sequence-dependent setup times, group scheduling, and renewable energy constraints. The objective is to minimize the total energy cost based on time-of-use electricity tariffs. Two mixed-integer linear programming models are developed, along with a decomposition-based heuristic algorithm for efficiently solving medium-size instances. Computational experiments show that the heuristic algorithm outperforms the developed models, with the time-interval index model exhibiting superior performance compared to the time-unit index model. Sensitivity analyses and economic performance evaluation are also provided.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Hong-Bo Song, Jian Lin
Summary: The paper introduces a GP-HH algorithm to address the DAPFSP-SDST problem by using genetic programming to generate heuristic sequences and incorporating simulated annealing for local search, achieving effective solutions and improving upon existing benchmarks.
SWARM AND EVOLUTIONARY COMPUTATION
(2021)
Article
Computer Science, Artificial Intelligence
Yu Du, Junqing Li, Chengdong Li, Peiyong Duan
Summary: In this study, a DQN model is proposed to solve a multiobjective FJSP with crane transportation and setup times. The model optimizes makespan and total energy consumption simultaneously based on weighting approach. The DQN model uses 12 state features and seven actions to describe the scheduling process, and applies a novel structure in the DQN topology. Extensive computational tests and comparisons demonstrate the effectiveness and advantages of the proposed method in solving FJSP-CS.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2022)
Article
Automation & Control Systems
Ming Li, Deming Lei
Summary: This paper discusses the energy-efficient flexible job shop scheduling problem (EFJSP) with transportation and sequence-dependent setup times (SDST), and develops an imperialist competitive algorithm with feedback (FICA) to minimize makespan, total tardiness, and total energy consumption simultaneously. The FICA algorithm incorporates assimilation, adaptive revolution, solution transferring among empires, and reinforced search. Extensive experiments demonstrate that FICA provides promising results for EFJSP with transportation and SDST.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2021)
Article
Automation & Control Systems
Fuqing Zhao, Tao Jiang, Ling Wang
Summary: Green manufacturing has gained increasing attention in the context of carbon peaking and carbon neutrality. Distributed production is prevalent in various manufacturing industries due to globalization. This article addresses the energy-efficient distributed no-wait flow-shop scheduling problem with sequence-dependent setup time (DNWFSP-SDST) for minimizing makespan and total energy consumption (TEC). A mixed-integer linear programming model is formulated, and a cooperative meta-heuristic algorithm based on Q-learning (CMAQ) is proposed. The experimental results demonstrate that CMAQ outperforms state-of-the-art comparison algorithms in solving energy-efficient DNWFSP-SDST.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Computer Science, Hardware & Architecture
Mahdi Jemmali, Lotfi Hidri
Summary: This paper addresses the two-stage hybrid flow shop problem with setup times, which is NP-Hard and has important real-life applications in manufacturing and high performance-computing. The paper proposes a metaheuristic using genetic algorithm and three heuristics, and provides three lower bounds based on the relaxation method. An experimental result is discussed to evaluate the performance of the developed algorithms in terms of gap and running time.
COMPUTER SYSTEMS SCIENCE AND ENGINEERING
(2023)
Article
Engineering, Industrial
Jeffrey Schaller, Jorge M. S. Valente
Summary: This paper addresses the scheduling of jobs in a no-wait flow shop with the goal of minimizing total earliness and tardiness. Various dispatching heuristics and insertion improvement procedures are developed and tested, showing that the two-phase heuristics and insertion search improvement procedure can significantly improve performance.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2022)
Article
Engineering, Multidisciplinary
Marcelo Seido Nagano, Fernando Siqueira de Almeida, Hugo Hissashi Miyata
Summary: This article proposes an iterated greedy-with-local-search algorithm for the no-wait flowshop scheduling problem, which outperforms both the mathematical model and the best existing algorithm in terms of effectiveness and efficiency according to computational experiments and statistical analysis.
ENGINEERING OPTIMIZATION
(2021)
Article
Management
Chuanhui Xiong, Anna G. Devlin, Jatinder N. D. Gupta, Xiangrong Liu
Summary: Global electricity generation has been dominated by fossil fuel sources, particularly coal, over the past decade. The rising concerns over pollution emissions and growing commitment to environmental change have led to a surge in clean and renewable energy. However, the sharp reduction in the price of renewable energy technology like solar PV panels has created challenges for manufacturers and retailers, causing inefficiencies in supply chains.
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
(2022)
Article
Computer Science, Interdisciplinary Applications
Fernando Luis Rossi, Marcelo Seido Nagano
Summary: The distributed permutation flowshop scheduling problem (DPFSP) has been widely studied due to the complex production systems with mixed no-idle flowshops. Although the issue of identical factories with mixed no-idle flowshop environments has not been explored in literature, new solutions including MILP formulation, constructive heuristic, and iterated greedy algorithms have been proposed. Extensive experiments showed that the proposed methods outperformed existing approaches.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Automation & Control Systems
Levi R. Abreu, Roberto F. Tavares-Neto, Marcelo S. Nagano
Summary: In this paper, a new biased random key genetic algorithm with an iterated greedy local search procedure (BRKGA-IG) is proposed for solving open shop scheduling with routing by capacitated vehicles. The algorithm combines approximation and exact algorithms to achieve high-quality solutions in acceptable computational times. The extensive computational experiments demonstrate that the proposed metaheuristic BRKGA-IG outperforms all other tested methods, showing promise in solving large-sized instances for the new proposed problem.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2021)
Article
Engineering, Multidisciplinary
Levi Ribeiro de Abreu, Kennedy Anderson Guimaraes Araujo, Bruno de Athayde Prata, Marcelo Seido Nagano, Joao Vitor Moccellin
Summary: This article introduces a new variant of the open shop scheduling problem, known as the open shop scheduling problem with repetitions (OSSPR), which has many applications in automotive and maintenance activities. By presenting a mixed-integer linear programming model and a new constraint programming model, along with a new efficient variable neighbourhood search method, the NP-hard problem is effectively solved with excellent performance shown in computational results.
ENGINEERING OPTIMIZATION
(2022)
Article
Information Science & Library Science
Suzana Xavier Ribeiro, Marcelo Seido Nagano
Summary: This study investigates the relation between knowledge management and university-industry-government collaboration in influencing organizations' performance, focusing on the Brazilian context. An analytical model is proposed, considering structural, relational, cognitive, and contextual dimensions. The findings show that organizational structure, relationships, and cognition play important roles in knowledge flow and sharing, while the context also has an impact. Cultural differences, bureaucracy, and socio-economic reality are identified as main obstacles, while the presence of technology parks, incubators, government incentives, and geographical proximity are facilitators.
VINE JOURNAL OF INFORMATION AND KNOWLEDGE MANAGEMENT SYSTEMS
(2023)
Article
Computer Science, Interdisciplinary Applications
Vincent F. Yu, Meng Qiu, Jatinder N. D. Gupta
Summary: Supplier training is essential for enhancing their capabilities to meet OEMs' needs. This study used the MMOG/LE framework to identify training needs and design a curriculum, resulting in improved supplier capabilities perceptions after training. This demonstrates the effectiveness of supplier training in improving performance and success within a supply chain.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Green & Sustainable Science & Technology
Vincent F. Yu, Thi Huynh Anh Le, Jatinder N. D. Gupta
Summary: This paper investigates the sustainable microgrid design problem with multiple types of demand areas, peer-to-peer energy trading, and seasonal factors. By developing a fuzzy multi-objective programming model and applying a genetic algorithm, the proposed model achieves significant improvements in increasing total profit and reducing environmental costs.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2022)
Article
Mathematics
Chin-Chia Wu, Jatinder N. D. Gupta, Win-Chin Lin, Shuenn-Ren Cheng, Yen-Lin Chiu, Juin-Han Chen, Long-Yuan Lee
Summary: This paper addresses the customer order scheduling problem involving two agents in uncertain environments. It proposes a branch-and-bound algorithm and several heuristics to find optimal or approximate solutions. The empirical evaluation demonstrates the effectiveness of the proposed methods in finding good solutions.
Article
Computer Science, Interdisciplinary Applications
Chunhao Li, Feng Wang, Jatinder N. D. Gupta, Tsuiping Chung
Summary: This paper investigates the problem of scheduling jobs on parallel batch processing machines with incompatible job families, non-identical job sizes, arbitrary job release times, and machine capacity constraints. It proposes a new algorithm that can obtain better solutions than existing algorithms.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Engineering, Industrial
Ming He, Qiuhua Tang, Jatinder N. D. Gupta, Di Yin, Zikai Zhang
Summary: This paper proposes a solution to the EMU first-level maintenance shunting scheduling problem with flexible maintenance routes in a stub-end depot. By formulating a multi-objective MILP model and using a heuristic-based enhanced particle swarm optimization algorithm (EPSO), an approximate optimal schedule is achieved. Experimental results demonstrate the effectiveness and efficiency of the algorithm.
FLEXIBLE SERVICES AND MANUFACTURING JOURNAL
(2023)
Review
Computer Science, Interdisciplinary Applications
Mohammad Shehab, Muhannad A. Abu-Hashem, Mohd Khaled Yousef Shambour, Ahmed Izzat Alsalibi, Osama Ahmad Alomari, Jatinder N. D. Gupta, Anas Ratib Alsoud, Belal Abuhaija, Laith Abualigah
Summary: This article provides a comprehensive review of the Bat algorithm (BA) and evaluates its characteristics in comparison with other optimization algorithms. It highlights the performance and variations of BA in different applications and suggests future research directions.
ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING
(2023)
Article
Engineering, Industrial
Hugo Hissashi Miyata, Marcelo Seido Nagano, Jatinder N. D. Gupta
Summary: This article incorporates maintenance operations into the blocking flow shop to minimize total completion time and maintenance costs. It develops a mixed integer linear programming and procedures for job sequence with maintenance. The study adapts different algorithms to solve small, medium, and large sets of instances, and evaluates their performance based on trade-off between solution quality and computational time.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Green & Sustainable Science & Technology
Vincent F. Yu, Thi Huynh Anh Le, Jatinder N. D. Gupta
Summary: Sustainable microgrid is a feasible approach to handle environmental impacts and satisfy customer demand. However, the installation rate has been limited due to high initial investment cost. This paper investigates the effect of government subsidies, peer-to-peer energy trading, financial factors, and demand elasticity coefficient on sustainable microgrid design.
Article
Automation & Control Systems
Ming He, Qiuhua Tang, Jatinder N. D. Gupta, Zikai Zhang, Jun Cao
Summary: This study proposes a robust scheduling model for first-level maintenance of electric multiple units in railway systems. An adaptive iterative local search algorithm is developed to solve this model. The proposed model considers flexible maintenance routes, train shunting conflicts, and track occupation conflicts, and includes uncertain parameters in objective functions and constraints. The algorithm incorporates problem-specific neighborhood structures, a variable neighborhood descent method, and an adaptive perturbation mechanism to achieve a trade-off between robustness and efficiency.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Computer Science, Interdisciplinary Applications
Xiaolin Wang, Liyi Zhan, Yong Zhang, Teng Fei, Ming-Lang Tseng
Summary: This study proposes an environmental cold chain logistics distribution center location model to reduce transportation costs and carbon emissions. It also introduces a hybrid arithmetic whale optimization algorithm to overcome the limitations of the conventional algorithm.
COMPUTERS & INDUSTRIAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
Hong-yu Liu, Shou-feng Ji, Yuan-yuan Ji
Summary: This study proposes an architecture that utilizes Ethereum to investigate the production-inventory-delivery problem in Physical Internet (PI), and develops an iterative heuristic algorithm that outperforms other algorithms. However, due to gas prices and consumption, blockchain technology may not always be the optimal solution.
COMPUTERS & INDUSTRIAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
Paraskevi Th. Zacharia, Elias K. Xidias, Andreas C. Nearchou
Summary: This article discusses the assembly line balancing problem in production lines with collaborative robots. Collaborative robots have the potential to improve automation, productivity, accuracy, and flexibility in manufacturing. The article explores the use of a problem-specific metaheuristic to solve this complex problem under uncertainty.
COMPUTERS & INDUSTRIAL ENGINEERING
(2024)
