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
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
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
Computer Science, Artificial Intelligence
Yuan-Zhen Li, Quan-Ke Pan, Ruben Ruiz, Hong-Yan Sang
Summary: This paper studies the distributed assembly mixed no-idle permutation flowshop scheduling problem (DAMNIPFSP) with the objective of minimizing total tardiness. An improved Iterated Greedy algorithm named RIG (Referenced Iterated Greedy) is proposed, which includes two novel destruction methods, four new reconstruction methods, and six new local search methods based on the characteristics of DAMNIPFSP. Experimental results show that RIG algorithm is a state-of-the-art procedure for DAMNIPFSP with the total tardiness criterion.
KNOWLEDGE-BASED SYSTEMS
(2022)
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
Computer Science, Interdisciplinary Applications
Hande Oztop, M. Fatih Tasgetiren, Levent Kandiller, Quan-Ke Pan
Summary: This study addresses the no-idle permutation flowshop scheduling problem (NIPFSP) and proposes MILP and CP models as well as IG_RL and ILS_RL algorithms. The performance of these methods is compared with existing approaches, and the results show that the proposed methods perform well on certain instances.
COMPUTERS & OPERATIONS RESEARCH
(2022)
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
Computer Science, Interdisciplinary Applications
Peng Wu, Yun Wang, Junheng Cheng, Yantong Li
Summary: This paper investigates a new bi-objective parallel machine scheduling and location problem and proposes a more efficient solution method. Experimental results show that the proposed method obtains more Pareto-optimal solutions and is faster in computation.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Engineering, Industrial
Jinsheng Gao, Xiaomin Zhu, Kaiyuan Bai, Runtong Zhang
Summary: This paper addresses the no-wait job shop scheduling problem with due date and subcontracting cost constraints, introducing two mathmatical models to find solutions for the problem.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2022)
Article
Engineering, Chemical
Ismet Karacan, Ozlem Senvar, Serol Bulkan
Summary: This paper addresses the no-wait flow shop problem with earliness and tardiness objectives, which is proven to be NP-hard. Previous studies on this problem mainly focused on familiar objectives, while the use of both earliness and tardiness objectives has been less explored. A novel methodology for the parallel simulated annealing algorithm is proposed to overcome the runtime drawback of classical simulated annealing and enhance its robustness.
Article
Management
Andre Bergsten Mendes, Filipe Pereira Alvelos
Summary: This study addresses the problem of minimizing the burned area and the number of deployed resources by determining the optimal locations for fire suppression resources in a gridded network landscape, considering the time delay caused by resource deployment. A novel iterated local search meta-heuristic is proposed and validated using a mixed integer programming model. The study also presents a systematic literature review on deterministic optimization models for fire suppression, highlighting the effectiveness of approximate collaborative approaches.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
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
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
Management
Alessandro Agnetis, Ben Hermans, Roel Leus, Salim Rostami
Summary: This paper discusses a problem of determining the state of a system through costly tests before a deadline, as well as a related search problem with multiple searchers aiming to find a target before a deadline. Both problems are shown to be NP-hard and various algorithms are proposed to tackle them effectively. Extensive computational experiments suggest that different formulations perform better in different scenarios, and a local search procedure is shown to be effective in finding near-optimal solutions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Computer Science, Interdisciplinary Applications
Andrea Balogh, Michele Garraffa, Barry O'Sullivan, Fabio Salassa
Summary: This paper considers the No-idle Permutation Flowshop Scheduling Problem (NPFSP) with a total tardiness criterion, and presents two Mixed Integer Linear Programming (MILP) formulations based on positional and precedence variables. Six local search procedures are studied, which explore two different neighborhoods by exploiting the MILP formulations. Computational experiments show that two of the proposed procedures outperform the state-of-the-art metaheuristic, updating a significant percentage of the best known solutions in Taillards' benchmark.
COMPUTERS & OPERATIONS RESEARCH
(2022)
