Article
Computer Science, Artificial Intelligence
Morteza Babazadeh Shareh, Shirin Hatami Bargh, Ali Asghar Rahmani Hosseinabadi, Adam Slowik
Summary: The open shop scheduling problem is an NP-hard problem, requiring high time complexity to obtain optimal solutions, hence heuristic techniques are used. This paper investigates the tasks scheduling problem in open shops using the Bat Algorithm, with designed heuristic functions to increase convergence rate. Results show that the proposed BA performs better in all cases and can generate the best solutions.
NEURAL COMPUTING & APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Ying Sun, Jeng-Shyang Pan, Pei Hu, Shu-Chuan Chu
Summary: This paper introduces the Equilibrium Optimizer (EO) algorithm and the Enhanced Equilibrium Optimizer (EEO) algorithm based on communication strategies for solving the Job Shop Scheduling Problem (JSSP). Experimental results show that the improved algorithm has made significant improvements in solving JSSP.
JOURNAL OF INTELLIGENT MANUFACTURING
(2023)
Article
Computer Science, Artificial Intelligence
Wenwu Han, Qianwang Deng, Guiliang Gong, Like Zhang, Qiang Luo
Summary: This study focuses on a new realistic hybrid flow shop scheduling problem with worker constraint (HFSSPW) and proposes seven multi-objective evolutionary algorithms to solve the problem, incorporating the earliest due date (EDD) rule into the heuristic decoding methods. The computational results demonstrate the excellent performance of the proposed algorithms in terms of makespan objective.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Interdisciplinary Applications
Saba Aghighi, Seyed Taghi Akhavan Niaki, Esmaeil Mehdizadeh, Amir Abbas Najafi
Summary: This paper presents a mixed-integer linear programming model for scheduling problems in an open-shop manufacturing system with reverse flows, aiming to minimize the maximum completion time of all jobs on all machines. A Vibration Damping-based Optimization algorithm and Taguchi experimental design approach are utilized to solve large-scale problems efficiently and improve performance. The computational results show that the VDO algorithm outperforms other optimization algorithms like SA, CS, ACO, HAS, ICA, and BA.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
Fangfang Zhang, Yi Mei, Su Nguyen, Mengjie Zhang, Kay Chen Tan
Summary: This paper proposes a novel surrogate-assisted evolutionary multitask algorithm via GP to share useful knowledge between different scheduling tasks to improve training efficiency and effectiveness. Phenotypic characterization is used to measure the behaviors of scheduling rules and build a surrogate for each task. The proposed algorithm successfully improves the quality of scheduling heuristics for all scenarios.
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
(2021)
Article
Computer Science, Artificial Intelligence
Mohamed Kurdi
Summary: This work proposes a new metaheuristic algorithm called ACONEH for open shop scheduling problem with the goal of improving the exploration capability of ant colony optimization and solving OSSP more effectively. The algorithm utilizes a new heuristic information approach that incorporates randomness, diversity, and improvability. Experimental results show that ACONEH achieves significant improvements in reducing the makespan of OSSP compared to traditional methods.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Engineering, Multidisciplinary
Kelvin Ching Wei Lim, Li-Pei Wong, Jeng Feng Chin
Summary: The flexible job-shop scheduling problem (FJSP) is common in high-mix industries. This study proposes a simulated-annealing-based hyper-heuristic algorithm (SA-HH) to solve the problem and investigates two variants. The experimental results show that the method performs well on most instances.
ENGINEERING OPTIMIZATION
(2023)
Article
Management
Ata Atay, Pedro Calleja, Sergio Soteras
Summary: This paper applies game theory to open shop scheduling problems, assigning the maximum cost savings to each coalition through admissible rearrangements of job operations. It provides a core allocation rule for games arising from unit open shop scheduling problems and includes two counterexamples to sharpen the bounds of balanced games.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Automation & Control Systems
ZiYan Zhao, MengChu Zhou, ShiXin Liu
Summary: Iterated greedy algorithm (IGA), developed in 2007, is widely used for flow-shop scheduling problems (FSPs) in production scheduling. Various FSPs have been solved using IGA-based methods, including basic IGA, variants, and hybrid algorithms. Over 100 articles related to IGA and FSPs have been published, highlighting the significance and potential of this algorithm in optimization.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2022)
Article
Computer Science, Artificial Intelligence
Fangfang Zhang, Yi Mei, Su Nguyen, Mengjie Zhang
Summary: The article proposes a recombinative guidance mechanism to improve the quality of offspring in genetic programming, preserving promising building blocks from one parent and incorporating good building blocks from the other. This approach significantly outperforms state-of-the-art algorithms in terms of both final test performance and convergence speed across various scenarios.
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
(2021)
Article
Computer Science, Artificial Intelligence
Suhaila Saidat, Ahmad Kadri Junoh, Wan Zuki Azman Wan Muhamad, Zainab Yahya
Summary: This paper focuses on solving the job shop scheduling problem of factories by proposing new methods and models to improve production efficiency and worker flexibility. Through the use of genetic algorithms and other methods, the study successfully reduced the overall operation time of products and improved worker flexibility in terms of waiting times.
NEURAL COMPUTING & APPLICATIONS
(2022)
Article
Computer Science, Artificial Intelligence
Yahong Yang, Xun Li
Summary: This paper addresses the distributed assembly blocking flow shop scheduling problem and proposes a knowledge-driven constructive heuristic algorithm. Three different kinds of neighborhood knowledge are designed based on problem characteristics, and the algorithm's superior performance is verified on benchmark instances.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Mathematics
Xiaowu Chen, Guozhang Jiang, Yongmao Xiao, Gongfa Li, Feng Xiang
Summary: An intelligent manufacturing trend is identified within the steel industry, proposing a cyber-physical system framework for steel production scheduling. The framework utilizes an ontology-based knowledge model and heuristic rules for dynamic scheduling, incorporating a genetic programming algorithm and learning-based high-level selection strategy to address scheduling issues caused by production disturbances. The algorithm's performance is validated through simulation.
Article
Operations Research & Management Science
Mohamadreza Dabiri, Mehdi Yazdani, Bahman Naderi, Hassan Haleh
Summary: This paper tackles the hybrid flow shop scheduling problem by minimizing the total tardiness cost and rejected job cost through job rejection as a single-objective problem. It presents a mixed-integer linear programming model and innovative heuristic algorithms along with meta-heuristics for solving large-sized problems effectively. Different encoding and decoding methods are adapted to algorithms to ensure efficiency of the solutions based on schedules. Results demonstrate the effectiveness of the mathematical model and proposed algorithms in scheduling the production system of a real-world hybrid flow shop in the tile industry. Additionally, the study explores the efficacy of job rejection and compares single-objective and bi-objective approaches on small and large-sized problems.
OPERATIONAL RESEARCH
(2022)
Article
Engineering, Chemical
Xiang Tian, Xiyu Liu
Summary: The study introduces a new hybrid heuristic algorithm to solve the JSSP problem and achieves good results by improving genetic algorithms, modifying particle swarm optimization, and local search methods.
Article
Engineering, Multidisciplinary
Fardin Ahmadizar, Jafar Eteghadipour
ENGINEERING OPTIMIZATION
(2017)
Article
Computer Science, Interdisciplinary Applications
A. Azadeh, H. Habibnejad-Ledari, S. Abdolhossein Zadeh, M. Hosseinabadi Farahani
INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING
(2017)
Article
Engineering, Multidisciplinary
Fardin Ahmadizar, Zeinab Amiri
ENGINEERING OPTIMIZATION
(2018)
Article
Computer Science, Artificial Intelligence
Fardin Ahmadizar, Ahmad Rabanimotlagh, Jamal Arkat
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2017)
Article
Automation & Control Systems
Mahdieh Labani, Parham Moradi, Fardin Ahmadizar, Mahdi Jalili
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2018)
Article
Management
Mehdi H. Farahani, Milind Dawande, Haresh Gurnani, Ganesh Janakiraman
Summary: The study analyzes a supply-flexibility contract that benefits both suppliers and buyers, improving supply chain efficiency. Even if the buyer lets the supplier decide how to share supply risk, profits for both parties increase with the introduction of flexibility.
M&SOM-MANUFACTURING & SERVICE OPERATIONS MANAGEMENT
(2021)
Article
Computer Science, Interdisciplinary Applications
Shokufeh Zamani, Jamal Arkat, Seyed Taghi Akhavan Niaki, Fardin Ahmadizar
Summary: This research addresses the issue of locating facilities with immobile servers, considering congestion and server interruption as sources of uncertainty. The proposed model aims to maximize profit while minimizing the cost of the system. Two meta-heuristic algorithms, genetic algorithm and ant lion algorithm, are introduced to tackle the optimization problem. Results show the efficiency of the algorithms, with the ant lion algorithm demonstrating higher quality and convergence rate compared to the genetic algorithm.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Computer Science, Interdisciplinary Applications
Mahdyeh Shiri, Fardin Ahmadizar, Houra Mahmoudzadeh
Summary: A novel hybrid three-phase methodology for routing and scheduling in the home healthcare problem is proposed in this study, which includes a combinatorial approach, a multi-objective robust model, and the Nimbus method. A real-life case study from Iran validates the applicability of the proposed model and its solutions.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
Mahdyeh Shiri, Fardin Ahmadizar, Dhananjay Thiruvady, Hamid Farvaresh
Summary: To meet the growing demand for home health care, especially during diseases like Covid-19, the design and planning of home health care systems are of great importance. This study proposes a multi-objective mixed-integer linear model for a home health care network, considering the opening of health centers and the routing and scheduling based on efficiency and corporate social responsibility. A novel aspect of this study is the consideration of social responsibility and efficiency in terms of time, energy, and mismanagement of budgets. The proposed approach shows efficiency in different instances within reasonable time frames and highlights the role of decision-makers' preferences in human resource planning and regional development.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Engineering, Multidisciplinary
Mohsen Torkashvand, Fardin Ahmadizar
Summary: In this article, a production-assembly scheduling problem is addressed, which consists of three steps including production operation, assembly operation, and post-assembly operation in parallel factories. The problem is NP hard and requires a mixed integer linear programming algorithm for small-sized problems, and a hybrid metaheuristic algorithm for large-sized problems. The proposed HQSD algorithm combining QPSO, SPT, and dominance rules outperforms other algorithms.
ENGINEERING OPTIMIZATION
(2023)
Article
Engineering, Multidisciplinary
M. Torkashvand, F. Ahmadizar, H. Farughi
Summary: This paper considers a new three stage production-assembly problem and proposes a MILP model and an improved genetic algorithm to solve it. The efficiency and effectiveness of the algorithm are evaluated through sensitivity analysis.
INTERNATIONAL JOURNAL OF ENGINEERING
(2022)
Article
Engineering, Multidisciplinary
L. Izadi, F. Ahmadizar, J. Arkat
INTERNATIONAL JOURNAL OF ENGINEERING
(2020)
Article
Engineering, Multidisciplinary
M. Soolaki, J. Arkat, F. Ahmadizar
INTERNATIONAL JOURNAL OF ENGINEERING
(2018)
Article
Computer Science, Interdisciplinary Applications
A. Azadeh, S. Elahi, M. Hosseinabadi Farahani, B. Nasirian
COMPUTERS & INDUSTRIAL ENGINEERING
(2017)
Article
Engineering, Multidisciplinary
A. Azadeh, S. Motevali Haghighi, M. Hosseinabadi Farahani, R. Yazdanparast
WORLD JOURNAL OF ENGINEERING
(2016)