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
Yarong Chen, Ya-Chih Tsai, Fuh-Der Chou
Summary: This paper focuses on the hybrid flow shop scheduling problem and proposes a new mixed integer programming model and two new lower bounds based on the bin-packing concept. The proposed model is compared with existing models using two sets of small and small-to-medium problems, and the effectiveness of the proposed lower bound is also demonstrated.
Article
Computer Science, Interdisciplinary Applications
Oliver Thomasson, Maria Battarra, Gunes Erdogan, Gilbert Laporte
Summary: This paper introduces the Twin-Robot Pallet Assignment and Scheduling Problem (TRPASP) and presents a mathematical model and four heuristic algorithms for solving the problem. The objective is to minimize the makespan, and computational experiments show that the best results are obtained using a parallel hybrid metaheuristic.
COMPUTERS & OPERATIONS RESEARCH
(2022)
Article
Computer Science, Artificial Intelligence
Weishi Shao, Zhongshi Shao, Dechang Pi
Summary: This paper studies a distributed heterogeneous hybrid flow shop lot-streaming scheduling problem (DHHFLSP) with the minimization of makespan. The mixed-integer linear programming model (MILP) of DHHFLSP is established, and eighteen constructive heuristics and an iterated local search algorithm (ILS) are designed to solve the problem. The comparisons with several related algorithms on extensive testing instances demonstrate the effectiveness and efficiency of the ILS algorithm.
EXPERT SYSTEMS WITH APPLICATIONS
(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
Mathematics
Mohamed Abdel-Basset, Reda Mohamed, Mohamed Abouhawwash, Ripon K. Chakrabortty, Michael J. Ryan
Summary: In this research, a new approach based on the improved elitism continuous genetic algorithm is proposed to tackle the permutation flow shop scheduling problem. By combining different crossover and re-initialization strategies, the algorithm shows significant improvement in both exploitation and exploration aspects.
Article
Management
Janis Brammer, Bernhard Lutz, Dirk Neumann
Summary: This study presents a novel reinforcement learning approach for the permutation flow shop problem (PFSP) with multiple lines and demand plans. The approach generates job sequences iteratively and optimizes them using local search, outperforming existing methods on multi-line problems with short cutoff times.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Computer Science, Artificial Intelligence
Jabrane Belabid, Said Aqil, Karam Allali
Summary: This paper proposes a new method for solving the flow shop scheduling problem, which outperforms classical algorithms in terms of effectiveness and robustness. By utilizing a mixed integer linear programming model and a hybrid greedy algorithm based on the Nash equilibrium concept and genetic operators, the paper aims to approach the optimal solution of the scheduling problem.
APPLIED INTELLIGENCE
(2023)
Article
Computer Science, Artificial Intelligence
Yuting Wang, Yuyan Han, Quan-ke Pan, Huan Li, Yuhang Wang
Summary: In this study, 48 available MILP models and an efficient CP model are constructed by categorizing the constraints. The experimental results show that models 24 and 48 exhibit superior performance, highlighting the effectiveness of the hybrid modeling approach.
SWARM AND EVOLUTIONARY COMPUTATION
(2023)
Article
Chemistry, Multidisciplinary
Christos Gogos
Summary: This paper investigates the permutation flow-shop scheduling problem and its distributed version, proposing constraint programming models and a novel heuristic to solve them. Experimental results demonstrate the effectiveness of the approach and highlight the significance of the number of jobs in problem complexity.
APPLIED SCIENCES-BASEL
(2023)
Article
Mathematics, Applied
Augusto Ferraro, Daniel Alejandro Rossit, Adrian Toncovich
Summary: This study addresses the scheduling problem with learning effect in a flow shop configuration by proposing a linear approximation approach. The exponential curve representing the learning effect is approximated by a set of piecewise smooth lines. A MILP model is then generated based on this approximation scheme, which shows improvements of over 10% in terms of makespan compared to the MINLP solution.
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS
(2023)
Article
Automation & Control Systems
Yuxia Pan, Kaizhou Gao, Zhiwu Li, Naiqi Wu
Summary: This paper addresses a distributed lot-streaming permutation flow shop scheduling problem and proposes five meta-heuristics to solve it. Experimental results show that the artificial bee colony algorithm with improved strategies exhibits the best competitiveness for solving the problem with makespan criteria.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2023)
Article
Computer Science, Artificial Intelligence
Shih-Wei Lin, Chen-Yang Cheng, Pourya Pourhejazy, Kuo-Ching Ying
Summary: Scheduling problems are crucial in modern manufacturing, and an improved meta-heuristic algorithm, MTSA, has been proposed for Permutation Flowshop Scheduling Problem with Mixed-Blocking Constraints, outperforming existing methods.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Information Systems
Bilal Khurshid, Shahid Maqsood, Muhammad Omair, Biswajit Sarkar, Muhammad Saad, Uzair Asad
Summary: The paper proposes an Improved Evolution Strategy to tackle the Permutation Flow Shop Scheduling Problems, demonstrating significant reduction in makespan and strong robustness. Computational results from testing on benchmark problems as well as real-life manufacturing scenarios show the effectiveness of the proposed technique.
Article
Management
Karim Tamssaouet, Stephane Dauzere-Peres
Summary: This article presents a framework that unifies and generalizes well-known literature results on local search for job-shop and flexible job-shop scheduling problems. The proposed framework focuses on quickly ruling out infeasible moves and evaluating the quality of feasible neighbors, which are crucial for the success of local search approaches. It can be applied to any scheduling problem with an appropriate defined neighborhood structure. The proposed framework introduces novel procedures for evaluating feasibility and estimating the value of objective functions for neighbor solutions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Computer Science, Information Systems
Zhicheng Cai, Xiaoping Li, Ruben Ruiz
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2019)
Article
Computer Science, Theory & Methods
Zhicheng Cai, Xiaoping Li, Ruben Ruiz, Qianmu Li
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2018)
Article
Computer Science, Theory & Methods
Long Chen, Xiaoping Li, Ruben Ruiz
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2018)
Article
Management
Ruben Ruiz, Quan-Ke Pan, Bahman Naderi
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2019)
Article
Automation & Control Systems
Yadi Wang, Xiaoping Li, Ruben Ruiz
IEEE TRANSACTIONS ON CYBERNETICS
(2019)
Article
Automation & Control Systems
Yamin Wang, Xiaoping Li, Ruben Ruiz, Shaochun Sui
IEEE TRANSACTIONS ON CYBERNETICS
(2018)
Article
Automation & Control Systems
Xiaoping Li, Yulu Jiang, Ruben Ruiz
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2018)
Article
Computer Science, Interdisciplinary Applications
Luis Fanjul-Peyro, Ruben Ruiz, Federico Perea
COMPUTERS & OPERATIONS RESEARCH
(2019)
Review
Management
Reza Zanjirani Farahani, Samira Fallah, Ruben Ruiz, Sara Hosseini, Nasrin Asgari
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2019)
Article
Management
Consuelo Parreno-Torres, Ramon Alvarez-Valdes, Ruben Ruiz
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2019)
Editorial Material
Biochemistry & Molecular Biology
Motoaki Seki
PLANT MOLECULAR BIOLOGY
(2019)
Article
Management
Shunji Tanaka, Kevin Tierney, Consuelo Parreno-Torres, Ramon Alvarez-Valdes, Ruben Ruiz
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2019)
Article
Management
Pedro Alfaro-Fernandez, Ruben Ruiz, Federico Pagnozzi, Thomas Stutzle
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2020)
Article
Automation & Control Systems
Haiyan Xu, Xiaoping Li, Ruben Ruiz, Haihong Zhu
Summary: This paper investigates single-machine group scheduling with nonperiodical maintenance and deteriorating effects, proposing batch-based heuristics and an iterated greedy algorithm as solutions. The study proves the NP-hardness of the problem and demonstrates the superiority of the proposed methods through comprehensive computational and statistical analyses.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Proceedings Paper
Computer Science, Interdisciplinary Applications
Yamin Wang, Xiaoping Li, Ruben Ruiz
PROCEEDINGS OF THE 2018 IEEE 22ND INTERNATIONAL CONFERENCE ON COMPUTER SUPPORTED COOPERATIVE WORK IN DESIGN ((CSCWD))
(2018)
