Article
Computer Science, Artificial Intelligence
Yuan-Zhen Li, Quan-Ke Pan, Jun-Qing Li, Liang Gao, M. Fatih Tasgetiren
Summary: This research focuses on distributed permutation flow shop scheduling problem with mixed no-idle constraints, using a mixed-integer linear programming model and an Adaptive Iterated Greedy algorithm with restart strategy. The algorithm shows excellent performance in large-scale experiments.
SWARM AND EVOLUTIONARY COMPUTATION
(2021)
Article
Computer Science, Interdisciplinary Applications
Ying-Ying Huang, Quan-Ke Pan, Jiang-Ping Huang, P. N. Suganthan, Liang Gao
Summary: This paper proposes an improved iterative greedy algorithm based on groupthink for solving the distributed assembly permutation flowshop scheduling problem with total flowtime criterion, and experimental results show that the proposed algorithm significantly outperforms other algorithms in comparison.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Automation & Control Systems
Heng-Wei Guo, Hong-Yan Sang, Xu-Jin Zhang, Peng Duan, Jun-Qing Li, Yu-Yan Han
Summary: In this paper, a discrete fruit fly optimization algorithm (DFFO) is proposed to solve the distributed permutation flowshop scheduling problem (DPFSP) with the goal of minimizing total flowtime. The DFFO algorithm adopts an initialization method that considers population quality and diversity, and it includes three perturbation operators and an improved reference local search method to improve its exploration and exploitation abilities. Experimental results on large-scale instances demonstrate the effectiveness of DFFO as a metaheuristic algorithm.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Computer Science, Artificial Intelligence
Hui Yu, Kai-Zhou Gao, Zhen-Fang Ma, Yu-Xia Pan
Summary: This study focuses on a significant distributed assembly permutation flowshop scheduling problem in practical manufacturing systems. Several meta-heuristics, including artificial bee colony, particle swarm optimization, genetic algorithm, and Jaya algorithm, and their variants are proposed to solve the problem. Experimental results demonstrate that the proposed Jaya algorithm with Q-learning-based local search performs well and achieves optimal solutions for the majority of benchmark instances.
SWARM AND EVOLUTIONARY COMPUTATION
(2023)
Article
Automation & Control Systems
Mustafa Avci
Summary: The distributed no-wait flowshop scheduling problem (DNWFSP) is a variant of the classical flowshop scheduling problem. An iterated local search (ILS) algorithm is proposed to solve the DNWFSP, which incorporates specialized local search and adaptively adjusted perturbation strength. The ILS is able to produce high-quality solutions in short computing times.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Automation & Control Systems
Fuqing Zhao, Zesong Xu, Ling Wang, Ningning Zhu, Tianpeng Xu, J. Jonrinaldi
Summary: This article investigates a distributed assembly no-wait flow-shop scheduling problem (DANWFSP) and proposes a population-based iterated greedy algorithm (PBIGA) to address the problem. The PBIGA is shown to be effective and outperforms state-of-the-art algorithms in terms of minimizing total flowtime. Experimental results on large-scale benchmark instances demonstrate the superiority of the proposed PBIGA.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Computer Science, Artificial Intelligence
Li Haoran, Li Xinyu, Gao Liang
Summary: With the development of globalization, distributed manufacturing has become a main mode of manufacturing. This paper addresses a distributed heterogeneous no-wait flowshop scheduling problem (DHNWFSP) and proposes a discrete artificial bee colony algorithm (DABC) to effectively solve it, considering the heterogeneity between factories in distributed flow-shop scheduling for the first time. The proposed DABC achieves the highest-quality solutions in comparison with state-of-art algorithms, as shown by numerical experiments for small and large-scale problems.
APPLIED SOFT COMPUTING
(2021)
Article
Computer Science, Interdisciplinary Applications
Mustafa Avci, Mualla Gonca Avci, Alper Hamzadayi
Summary: This article proposes a branch-and-cut algorithm for solving the DNWFSP problem. By combining with a heuristic algorithm and employing symmetry breaking constraints to strengthen the model, this algorithm can improve the solution effectiveness of the DNWFSP problem to a certain extent.
COMPUTERS & OPERATIONS RESEARCH
(2022)
Article
Metallurgy & Metallurgical Engineering
Hua Xuan, Qianqian Zheng, Bing Li, Xueyuan Wang
Summary: The paper presents a study on scheduling N jobs in a hybrid flowshop with unrelated parallel machines, proposing a novel genetic simulated annealing algorithm to address the problem effectively. The algorithm includes an adaptive adjustment strategy to avoid premature convergence and enhance search ability, along with a simulated annealing procedure for re-optimization of better individuals from the genetic algorithm solutions. Computational results show that the algorithm outperforms several heuristic algorithms reported in the literature.
ISIJ INTERNATIONAL
(2021)
Article
Engineering, Multidisciplinary
Bruno de Athayde Prata, Marcelo Seido Nagano
Summary: This study proposes an innovative iterated greedy algorithm for the no-wait permutation flowshop layout problem. The algorithm outperforms five other algorithms in terms of two performance measures.
ENGINEERING OPTIMIZATION
(2022)
Article
Automation & Control Systems
Hui Zhao, Quan-Ke Pan, Kai-Zhou Gao
Summary: This paper studies the distributed permutation flowshop group scheduling problem (DPFGSP) and proposes a cooperative population-based iterated greedy (CPIG) algorithm to minimize total flowtime (TF). The CPIG algorithm divides DPFGSP into two sub-problems and uses advanced technologies to address them. Experimental evaluation shows that the CPIG algorithm outperforms five state-of-the-art metaheuristics in the literature.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Computer Science, Artificial Intelligence
Chen-Yang Cheng, Pourya Pourhejazy, Kuo-Ching Ying, Yi-Hsiu Liao
Summary: This study successfully addressed the No-wait Flowshop Group Scheduling Problems, achieving a best-found solution rate of over 99.7% through the development of two metaheuristics. The results indicate that RMSA outperforms existing algorithms for solving the NWFGSP_SDST problem.
APPLIED SOFT COMPUTING
(2021)
Article
Management
Czeslaw Smutnicki, Jaroslaw Pempera, Grzegorz Bocewicz, Zbigniew Banaszak
Summary: This paper investigates the problem of cyclic scheduling in a manufacturing system, considering the flow of jobs with identical technological routes, no-wait constraints, and missing operations. The problem is decomposed into two sub-problems, and alternative methods are provided for finding the minimal cycle time and optimal processing order of jobs. A metaheuristic approach is used to solve the latter sub-problem. Experimental examination demonstrates the efficiency and quality of the proposed algorithm.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Automation & Control Systems
Shuai Chen, Quan-Ke Pan, Liang Gao, Hong-yan Sang
Summary: This paper proposes a population-based iterated greedy algorithm to solve the distributed blocking flowshop scheduling problem, which effectively combines constructive heuristic, offspring generation, and local search, outperforming existing algorithms in comprehensive experimental evaluation.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2021)
Article
Engineering, Industrial
Tuane Tonani Yamada, Marcelo Seido Nagano, Hugo Hissashi Miyata
Summary: The study proposes constructive methods to minimize total tardiness in production scheduling, with the HENLL algorithm using insertion logic showing the best performance. Additionally, a metaheuristic based on the iterated greedy search method is presented to significantly improve results obtained by the heuristics alone.
INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING COMPUTATIONS
(2021)
Article
Management
Fernando Luis Rossi, Marcelo Seido Nagano
Summary: This paper investigates the mixed no-idle flowshop scheduling problem with sequence-dependent setup times and makespan minimisation criterion. A mathematical formulation and a constructive heuristic are proposed for this new problem, and extensive experiments show that the new heuristic outperforms methods from the literature.
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
(2021)
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
Engineering, Industrial
Antonio Costa, Salvatore Cannella, Roberto R. Corsini, Jose M. Framinan, Sergio Fichera
Summary: In this paper, a two-echelon, two-product Supply Chain is investigated, considering the impact of product change-over time and machine breakdowns on production capacity. Experimental analysis reveals the variations in fill rate and inventory standard deviation. The study highlights the interaction between production planning model and replenishment strategy, which significantly affects the performance of the Supply Chain.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2022)
Article
Engineering, Industrial
Salvatore Cannella, Borja Ponte, Roberto Dominguez, Jose M. Framinan
Summary: Research indicates that POUT policies are valuable tools for enhancing the dynamics of closed-loop supply chains, with significant cost savings achievable in hybrid manufacturing/remanufacturing systems. To optimize the balance between order and inventory variability, factors such as cost structure and average return rate should be considered, with adjustments to the controllers' time constant necessary to adapt to increasing levels of circularity. Aligning the calibration of POUT controllers and forecasting methods is recommended to improve the economic performance of CLSCs.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2021)
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
Engineering, Industrial
Roberto Rosario Corsini, Antonio Costa, Salvatore Cannella, Jose M. Framinan
Summary: This study investigates the impact of different production control policies on Fill Rate in a two-product, two-echelon supply chain dynamic problem with production capacity. The results reveal that the Hedging Corridor Policy is the best strategy to increase the Fill Rate.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Operations Research & Management Science
Jose M. Framinan, Paz Perez-Gonzalez, Victor Fernandez-Viagas
Summary: This paper provides an overview of decision problems in Additive Manufacturing (AM) and classifies them, presenting the underlying OR techniques used to solve them. The aim is to raise awareness among the OR community and encourage active participation in this research area.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Operations Research & Management Science
R. R. Corsini, A. Costa, J. M. Framinan
Summary: This paper investigates the effectiveness of a new adaptive production control policy for a two-product, two-echelon supply chain with non-stationary customer demand. The proposed strategy, named Adaptive Hedging Corridor Policy, aims to maximize the fill rate by considering capacity constraints and disruptive events. A simulation model and experimental campaign are conducted to compare the proposed strategy with two alternatives. The results demonstrate the effectiveness of the new adaptive strategy in maximizing fill rate under non-stationary demand.
INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE AND ENGINEERING MANAGEMENT
(2023)
Article
Economics
Tiago Fernando Musetti, Alceu Gomes Alves Filho, Marcelo Seido Nagano, Ana Lucia Vitale Torkomian
Summary: This research contributes to the literature on strategic management in micro and small technology-based companies by identifying the main characteristics of strategic behavior. The qualitative research method used case studies to indicate that strategic behavior in these companies includes defining competitive and innovation strategies, allocating organizational resources to innovate and develop dynamic capabilities, and adapting to market demands to gain competitive advantages.
DIMENSION EMPRESARIAL
(2021)
Article
Engineering, Industrial
Tuane Tonani Yamada, Marcelo Seido Nagano, Hugo Hissashi Miyata
Summary: The study proposes constructive methods to minimize total tardiness in production scheduling, with the HENLL algorithm using insertion logic showing the best performance. Additionally, a metaheuristic based on the iterated greedy search method is presented to significantly improve results obtained by the heuristics alone.
INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING COMPUTATIONS
(2021)
Article
Management
Juliana Keiko Sagawa, Marcelo Seido Nagano
Summary: This paper investigates the relationships among integration, uncertainty, IQ and performance in the context of the production planning and control function, showing that integration positively affects planning performance, mediated by IQ and moderated by uncertainty.
REGE-REVISTA DE GESTAO
(2021)
Article
Management
Viviane Souza Vilela Junqueira, Marcelo Seido Nagano, Hugo Hissashi Miyata
REGE-REVISTA DE GESTAO
(2020)
