Article
Chemistry, Multidisciplinary
Fatima Abderrabi, Matthieu Godichaud, Alice Yalaoui, Farouk Yalaoui, Lionel Amodeo, Ardian Qerimi, Eric Thivet
Summary: This paper focuses on studying an optimization problem in a hospital supply chain and developing decision support models and algorithms for hospital catering production scheduling. By considering the production system as a flexible job shop system to minimize total flow time, a novel mathematical model and two metaheuristics are proposed for multi-product and multi-stage food production scheduling, showing significant improvements in production system performance.
APPLIED SCIENCES-BASEL
(2021)
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
Computer Science, Artificial Intelligence
Yuanyuan Zhang, Junqing Li, Ying Xu, Peiyong Duan
Summary: Inspired by the production model of pressure vessels for spacecraft, this study proposes a method to solve the sequence-dependent group flow shop scheduling problem. By designing a multi-population cooperative multi-objective evolutionary algorithm, with the combination of problem-specific heuristics and operators, high-quality solutions are generated and optimized. Experimental results demonstrate that the proposed method outperforms other algorithms in terms of diversity and convergence performance.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Interdisciplinary Applications
Fuqing Zhao, Zesong Xu, Haizhu Bao, Tianpeng Xu, Ningning Zhu, Jonrinaldi
Summary: This paper investigates the distributed blocking flow-shop sequence-dependent scheduling problem (DBFSDSP) considering production efficiency measures. Existing literature often overlooks energy efficiency indicators. To address this, a cooperative whale optimization algorithm (CWOA) is proposed to solve DBFSDSP. The algorithm defines a critical path, designs energy-saving operations for the non-critical path, accelerates operations for the critical path, and incorporates three acceptance criteria for multi-objective optimization. Experimental results show that CWOA outperforms other algorithms in terms of efficiency and significance in solving DBFSDSP.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Computer Science, Artificial Intelligence
Guiliang Gong, Jiuqiang Tang, Dan Huang, Qiang Luo, Kaikai Zhu, Ningtao Peng
Summary: This paper proposes a flexible job shop scheduling problem with discrete operation sequence flexibility and designs an improved memetic algorithm to solve it. Experimental results show that the algorithm outperforms other algorithms in terms of performance. The proposed model and algorithm can help production managers obtain optimal scheduling schemes considering operations with or without sequence constraints.
SWARM AND EVOLUTIONARY COMPUTATION
(2024)
Article
Engineering, Industrial
Hui-Yu Zhang, Shao-Hui Xi, Qing-Xin Chen, James MacGregor Smith, Ning Mao, Xiang Li
Summary: The study addresses the complex problem of performance modelling in integrated production and material handling systems. It proposes a decomposition method for computing system performance measures in a flexible flow shop model and successfully demonstrates its accuracy and efficiency through numerical experiments. Additionally, the study investigates and analyzes the properties of the system, particularly in material handling processes, providing a basis for system design and resource planning.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2021)
Article
Computer Science, Interdisciplinary Applications
Anzhen Peng, Longcheng Liu, Weifeng Lin
Summary: The study focuses on a two-stage flexible flow shop scheduling problem and proposes several approximation algorithms to minimize the maximum job completion time.
JOURNAL OF COMBINATORIAL OPTIMIZATION
(2021)
Article
Computer Science, Artificial Intelligence
Imma Ribas, Ramon Companys, Xavier Tort-Martorell
Summary: This paper addresses the scheduling problem in a parallel flow shop configuration with sequence-dependent setup times. The analysis of various iterated greedy algorithms led to the identification of an efficient algorithm to minimize maximum job completion time. Computational evaluation highlighted the efficiency of searching in different neighborhood structures and the significant impact of the initial solution on performance.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Yan Wang, Zhao-hong Jia, Xing-yi Zhang
Summary: This study addresses a multi-stage flexible flow shop scheduling problem with batch processing machines, aiming to minimize the makespan and total energy consumption. A hybrid meta-heuristic algorithm based on ant colony optimization and genetic algorithms is proposed to solve the problem, with extensive simulation experiments conducted to verify its effectiveness and efficiency.
SWARM AND EVOLUTIONARY COMPUTATION
(2022)
Article
Computer Science, Information Systems
Yilun Wang, Qianwen Zhu
Summary: This study proposes a hybrid algorithm to solve the flexible job shop scheduling problem, integrating genetic algorithm with tabu search and adopting effective encoding and decoding methods. Experimental results demonstrate the great performance of this algorithm in solving FJSP-SDST-LT.
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
Engineering, Manufacturing
Gregory A. Kasapidis, Dimitris C. Paraskevopoulos, Panagiotis P. Repoussis, Christos D. Tarantilis
Summary: This paper investigates flexible job shop scheduling problems with arbitrary precedence graphs, proposing rigorous mixed integer and constraint programming models as well as an evolutionary algorithm. Through the creation of a new heuristic solution framework and theorems, it addresses the challenges of considering makespan and precedence graph flexibility in scheduling.
PRODUCTION AND OPERATIONS MANAGEMENT
(2021)
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
Management
Liji Shen, Stephane Dauzere-Peres, Sohnke Maecker
Summary: This paper addresses the issue of energy efficient scheduling in a flexible job shop. It aims to minimize total energy cost under a time-of-use pricing scheme, while ensuring that the schedule does not exceed a maximum makespan. The problem is initially formulated as a mixed integer program and then extensively studied for the simpler case of a fixed sequence of operations. The derived properties of this specific problem are utilized to propose heuristic approaches and an iterative tabu search algorithm for the general problem. Computational experiments are conducted to evaluate the solution methods and potential energy cost savings based on flexibility of the makespan and time-of-use structures.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
Fantahun M. Defersha, Dolapo Obimuyiwa, Alebachew D. Yimer
Summary: In most published articles on flexible job shop scheduling problems (FJSP), the focus is primarily on the limited capacities of machines as the constraining resources. However, with the increasing adoption of numerically controlled machines with self-controlling capabilities, the role of machine operators has changed from performing sequential steps to becoming machine tenders. This paper proposes a mathematical model for a new setup operator constrained FJSP (SOC-FJSP), where setup operations are assumed to be detached. The proposed simulated annealing algorithm is developed to solve the mathematical model, and further extensions are made to account for sequence-dependent setup time and workload balancing among the setup operators.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Statistics & Probability
Narges Mahdavi-Nasab, Mostafa Abouei Ardakan, Mohammad Mohammadi
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
(2020)
Article
Computer Science, Interdisciplinary Applications
Hassan Zohali, Bahman Naderi, Mohammad Mohammadi, Vahid Roshanaei
COMPUTERS & OPERATIONS RESEARCH
(2019)
Article
Computer Science, Interdisciplinary Applications
Mohammad Saeid Atabaki, Alireza Arshadi Khamseh, Mohammad Mohammadi
COMPUTERS & INDUSTRIAL ENGINEERING
(2019)
Article
Computer Science, Interdisciplinary Applications
Mohammad Saeid Atabaki, Mohammad Mohammadi, Bahman Naderi
COMPUTERS & INDUSTRIAL ENGINEERING
(2020)
Article
Chemistry, Physical
Mohamadreza Fazli-Khalaf, Bahman Naderi, Mohammad Mohammadi, Mir Saman Pishvaee
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
(2020)
Article
Green & Sustainable Science & Technology
Mohammad Saeid Atabaki, Mohammad Mohammadi, Vahid Aryanpur
Summary: This paper aims to develop an integrated simulation-optimization decision support system for electricity generation planning. The results show that the broader deployment of wind turbine primarily, solar thermal subsequently, is the major source of difference in the sustainable expansion compared to business as usual (BAU). However, the findings indicate that even the extensive utilization of renewable energy sources cannot guarantee sustainability improvement all through the planning period. Supply-side plans should be appropriately supported by demand-side strategies.
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS
(2022)
Article
Computer Science, Artificial Intelligence
S. Fateme Attar, Mohammad Mohammadi, Seyed Hamid Reza Pasandideh, Bahman Naderi
Summary: This study focuses on addressing the Electric Vehicle Production Routing Problem through a mixed-integer linear programming model and developing two logic-based Benders Decomposition algorithms to solve the NP-hard problem. Experimental results demonstrate that the proposed algorithms outperform traditional MIP formulation and are efficient in finding high-quality solutions.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Engineering, Multidisciplinary
P. Maghzi, M. Mohammadi, S. H. R. Pasandideh, B. Naderi
Summary: Today, planning and scheduling problems have a great impact on improving organizational productivity and serving systems such as medical and healthcare providers. This study presents a multi-objective mathematical model to minimize operating room scheduling and the risk of using equipment. Time constraints and limited capacity of medical equipment are considered in the model, and a fuzzy uncertainty analysis is conducted. The research results indicate that the NSGA-II algorithm is more efficient in the operating room scheduling problem.
INTERNATIONAL JOURNAL OF ENGINEERING
(2022)
Proceedings Paper
Engineering, Electrical & Electronic
Mohammad Saeid Atabaki, Mohammad Mohammadi
Summary: Electricity supply planning is a complex problem, especially with the rapid development of power generation technologies. A model combining genetic algorithm, linear programming, and AHP-TOPSIS method was proposed to analyze Iran's power sector. Results show that solar PV and wind turbine technologies are promising for Iran's long-term power demand, while an environmentally sustainable plan would reduce CO2 and SO2 emissions and water usage, but increase land requirement. Expanding renewable energy capacity is crucial for maintaining a decreasing trend in CO2 emissions.
2021 29TH IRANIAN CONFERENCE ON ELECTRICAL ENGINEERING (ICEE)
(2021)
Article
Business, Finance
Masood Kiarashrad, Seyed Hamid Reza Pasandideh, Mohammad Mohammadi
Summary: This paper presents an integrated model of fleet assignment, airline scheduling, and ticket pricing in a competitive market network. Four essential factors influencing ticket pricing are considered in the model, which is formulated as a mixed-integer nonlinear programming and solved using tabu search metaheuristic method.
JOURNAL OF REVENUE AND PRICING MANAGEMENT
(2021)
Article
Green & Sustainable Science & Technology
Mohamadreza Fazli-Khalaf, Bahman Naderi, Mohammad Mohammadi, Mir Saman Pishvaee
Summary: This paper aims to design a sustainable and resilient tire closed-loop supply chain network based on a real case study in Iran. A new resiliency approach is proposed by extending efficient demand coverage plans to immune the network against disruptions. The developed model includes four objectives to minimize total costs, maximize customer demand coverage, enhance operational reliability, reduce CO2 emissions, and maximize social responsibility. Outputs confirm the accurate performance of the extended model and ensure its applicability in the real-world case study.
ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
(2021)
Article
Business, Finance
Masood Kiarashrad, Seyed Hamid Reza Pasandideh, Mohammad Mohammadi
Summary: This research analyzes the effect of airline and passenger factors on ticket pricing in a domestic market, finding that airport dominance and differences between full service carriers and low-cost carriers are key factors affecting ticket pricing. The presence of a flag airline as a price regulator in a route can also impact ticket prices.
JOURNAL OF REVENUE AND PRICING MANAGEMENT
(2021)
Article
Management
Mohammad Saeid Atabaki, Seyed Hamid Reza Pasandideh, Mohammad Mohammadi
JOURNAL OF MODELLING IN MANAGEMENT
(2020)
Article
Engineering, Multidisciplinary
B. Abbasi, A. Mirzazadeh, M. Mohammadi
Proceedings Paper
Engineering, Industrial
Parisa Maghzi, Mina Roohnavazfar, Mohammad Mohammadi, Bahman Naderi
PROCEEDINGS OF 2019 15TH IRAN INTERNATIONAL INDUSTRIAL ENGINEERING CONFERENCE (IIIEC)
(2019)
