Article
Computer Science, Interdisciplinary Applications
Damla Kizilay
Summary: This study focuses on the problem of disassembly line balancing, which involves sequence-dependent setup time and complex AND/OR precedence relations. The managerial impacts of this study are crucial for both environmental and industrial sustainability. The problem is solved using mixed-integer linear programming and constraint programming models, and compared with a simulated annealing metaheuristic.
COMPUTERS & OPERATIONS RESEARCH
(2022)
Article
Computer Science, Artificial Intelligence
Hamid Yilmaz
Summary: This paper addresses the Assembly Line Worker Assignment and Balancing Problem (ALWABP) with sequence-dependent setup times between tasks, proposing a mixed integer linear programming model and a simulated annealing algorithm to solve the NP-hard problem. Experimental results on 640 benchmark problems show that the proposed algorithm is more effective and robust for a large set of benchmark problems compared to the mixed integer programming model.
Article
Computer Science, Artificial Intelligence
Zixiang Li, Mukund Nilakantan Janardhanan, S. G. Ponnambalam
Summary: This study investigates the cost-oriented robotic assembly line balancing problem, including purchasing cost and setup time optimization, by developing a mixed-integer linear programming model. The proposed IMABC algorithm introduces new employed bee phase and scout phase to enhance exploration and exploitation.
JOURNAL OF INTELLIGENT MANUFACTURING
(2021)
Article
Chemistry, Multidisciplinary
Francesco Pilati, Emilio Ferrari, Mauro Gamberi, Silvia Margelli
Summary: This paper proposes a new mixed-integer programming model to simultaneously optimize line efficiency, length, and workload smoothness. A customized procedure based on simulated annealing algorithm is developed and applied to the real assembly line of European sports car manufacturers, showing remarkable performances in terms of solution quality and computation time. The proposed approach serves as a practical reference for efficient multi-manned assembly line design in industrial fields.
APPLIED SCIENCES-BASEL
(2021)
Article
Computer Science, Artificial Intelligence
Chin-Chia Wu, Win-Chin Lin, Xin-Gong Zhang, Dan-Yu Bai, Yung-Wei Tsai, Tao Ren, Shuenn-Ren Cheng
Summary: This study explores the importance of setup times in scheduling decisions in real-world industrial environments, as well as the issue of job processing times in the face of various uncertainties. By introducing a single-machine scheduling problem and various algorithms, and optimizing solutions to find the best approach.
COMPLEX & INTELLIGENT SYSTEMS
(2021)
Article
Multidisciplinary Sciences
Amy H. I. Lee, He-Yau Kang, Chong-Lin Chen
Summary: The study considers four objectives and uses a fuzzy multi-objective linear programming model and a genetic algorithm model to solve the assembly line balancing problem. In practical cases, the models can efficiently solve small-scale problems, while the genetic algorithm can obtain good solutions for large-scale problems in a short time.
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
Computer Science, Interdisciplinary Applications
Thiago Cantos Lopes, Adalberto Sato Michels, Celso Gustavo Stall Sikora, Nadia Brauner, Leandro Magatao
Summary: This study introduces an economically robust solution to the assembly line balancing problem by designing assembly lines that allow flexible alternation between cycle times in response to demand fluctuations. A mixed-integer linear programming model is used to describe the problem, with a heuristic procedure implemented to quickly generate high-quality solutions.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Engineering, Industrial
Kuo-Ching Ying, Pourya Pourhejazy, Chen-Yang Cheng, Ren-Siou Syu
Summary: This research extends the distributed assembly permutation flowshop scheduling problem to account for flexible assembly and sequence-independent setup times in a supply chain-like setting. Constructive heuristic and customised metaheuristic algorithms are proposed to solve this emerging scheduling extension, demonstrating higher performance compared to existing algorithms.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Hong-Bo Song, Jian Lin
Summary: The paper introduces a GP-HH algorithm to address the DAPFSP-SDST problem by using genetic programming to generate heuristic sequences and incorporating simulated annealing for local search, achieving effective solutions and improving upon existing benchmarks.
SWARM AND EVOLUTIONARY COMPUTATION
(2021)
Article
Computer Science, Artificial Intelligence
Kaipu Wang, Xinyu Li, Liang Gao, Peigen Li, Surendra M. Gupta
Summary: In this paper, a parallel partial disassembly line balancing model is established, and a new genetic simulated annealing algorithm is proposed to optimize the model, which can improve the disassembly efficiency and economic benefits. The proposed algorithm shows superior performance in practical applications.
APPLIED SOFT COMPUTING
(2021)
Article
Engineering, Industrial
Thiago Cantos Lopes, Nadia Brauner, Leandro Magatao
Summary: The study shows that fractional allocations often lead to better resource utilization with relatively low costs. Higher space requirement costs are typically one-time investments, while lower cycle time represents fundamentally continuous gains.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2022)
Article
Engineering, Multidisciplinary
Sehmus Aslan
Summary: This study proposes a new mathematical model and algorithm for balancing mixed-model robotic two-sided assembly lines, aiming to minimize the cycle time by considering sequence-dependent setup times. Experimental results show that the proposed method achieves promising results.
OPTIMIZATION AND ENGINEERING
(2023)
Article
Engineering, Chemical
Yuting Xu, Bin Shi
Summary: This study focuses on the unrelated parallel machine scheduling problem and proposes a mathematical model aimed at reducing completion time. An improved lineup competition algorithm is introduced, along with heuristic workpiece allocation rules and variation strategies to enhance search accuracy and rate. The method shows superior effectiveness and stability compared to other approaches, making it competitive in solving the UPMST problem.
Article
Engineering, Industrial
Pourya Pourhejazy, Chen-Yang Cheng, Kuo-Ching Ying, Su-Yuan Lin
Summary: This study contributes to the literature of distributed scheduling by developing an original Mixed-Integer Linear Programming (MILP) formulation and extending the Iterated Greedy algorithm to solve the Distributed Two-Stage Assembly Flowshop Scheduling Problem with Sequence-Dependent Setup Times. Extensive numerical tests show that the Improved Iterated Greedy (IIG) algorithm yields the best solution in large-scale instances, with statistical analysis confirming its superiority over other algorithms.
JOURNAL OF MANUFACTURING SYSTEMS
(2021)
Article
Engineering, Multidisciplinary
Kamran Forghani, S. M. T. Fatemi Ghomi, Reza Kia
Summary: This article discusses the importance of Cell Formation (CF) and Group Layout (GL) in designing a cellular manufacturing system and proposes an integrated model that simultaneously considers energy consumption, assembly aspects, and process routing to minimize material handling costs and electric energy consumption. Through a case study, managerial insights are provided, and a hybrid solution approach is proposed for the complex problem. Computational results demonstrate the superiority of this hybrid approach over traditional methods.
ENGINEERING OPTIMIZATION
(2022)
Article
Transportation
Mehrdad Gharib, Seyyed Mohammad Taghi Fatemi Ghomi, Fariborz Jolai
Summary: This paper presents a mathematical model for post-disaster planning with human casualties, aiming to guide the proper utilization of emergency resources. The model focuses on maximizing patient survival probability, minimizing treatment completion time, and reducing operational costs. Two innovative meta-heuristic algorithms are proposed to tackle the NP-hardness of the problem, along with a case study and computational analysis for evaluation.
TRANSPORTMETRICA A-TRANSPORT SCIENCE
(2022)
Article
Business
Ehsan Khanmohammadi, Hossein Safari, Mostafa Zandieh, Behnam Malmir, Erfan Babaee Tirkolaee
Summary: This article introduces an integrated framework using balanced scorecard, system dynamics simulation, case-based reasoning method, and adaptive neuro-fuzzy inference system model to help strategy managers determine an organization's strategy. A real-world case study was conducted to validate the methodology's applicability and yielded appropriate strategies in line with managers' objectives.
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT
(2022)
Article
Engineering, Industrial
Hamed Jafar-Zanjani, Mostafa Zandieh, Mani Sharifi
Summary: The study discusses the importance of organizations shifting from centralized to decentralized structures and developing multi-factor production networks in the global business market. By proposing a bi-objective optimization model and utilizing robust programming and heuristic methods for maintenance planning and scheduling, as well as resilience strategies for network disruptions, the uncertainty of input parameters is effectively addressed.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)
Article
Environmental Sciences
Ali Sibevei, Adel Azar, Mostafa Zandieh, Seyed Mohammad Khalili, Maziar Yazdani
Summary: The study found that by using the newly proposed approach, supply chain risks could be assessed more effectively, especially when the number of risks is large. Resolving the root risks of the blood supply chain frequently requires management skills. This paper proposes a new systemic approach that offers a fresh perspective on supply chain risk management.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
(2022)
Article
Green & Sustainable Science & Technology
Navid Salmanzadeh-Meydani, S. M. T. Fatemi Ghomi, Seyedhamidreza Shahabi Haghighi, Kannan Govindan
Summary: This paper presents a method for evaluating the sustainability performance of an organization using PCA, NT, and statistical analysis. The results show that the factors related to the outcomes are of great importance for organizational performance, and there has been a decline in sustainability performance in recent years.
ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
(2023)
Article
Engineering, Industrial
Mohammad Ali Nikouei, Mostafa Zandieh, Maghsoud Amiri
Summary: This paper incorporates preventive maintenance activities into the two-stage assembly flow-shop scheduling problem and proposes three maintenance policies. Two hybrid optimization methods are used to find proper job sequencing, with variable neighborhood search with simulated annealing algorithm showing superior solution quality and computational time.
JOURNAL OF INDUSTRIAL AND PRODUCTION ENGINEERING
(2022)
Article
Management
Mohsen Abdoli, Mostafa Zandieh, Sajjad Shokouhyar
Summary: This study determines the optimal queuing system capacity by analyzing the properties of the queuing system and appointment window, aiming to minimize the total costs. The findings can guide the management decisions of both public and private healthcare centers.
JOURNAL OF MODELLING IN MANAGEMENT
(2023)
Article
Operations Research & Management Science
M. Jenabi, S. M. T. Fatemi Ghomi, S. A. Torabi, Moeen Sammak Jalali
Summary: This paper presents a stochastic programming model and a combined solution algorithm to address the integrated resource planning problem in electric power systems, taking into account uncertainties and implementing on IEEE test systems.
Article
Engineering, Industrial
Vahid Kayvanfar, M. Zandieh, Mehrdad Arashpour
Summary: This research investigates the economic lot scheduling problem and proposes a hybrid algorithm that outperforms other algorithms in terms of solution quality and diversity.
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE-OPERATIONS & LOGISTICS
(2022)
Article
Engineering, Chemical
Navid Salmanzadeh-Meydani, S. M. T. Fatemi Ghomi, Seyedhamidreza Shahabi Haghighi, Kannan Govindan
Summary: This paper presents a quantitative approach to evaluate the resilience of organizations in sudden-onset disasters, taking into account preparedness actions. The concept of the resilience triangle is expanded and the gradual improvement of functionality level is examined as a type of preparedness action. Measures of robustness and rapidity are used to indicate the loss of functionality and recovery time, while resourcefulness and redundancy measures are used to improve disaster resilience. Mathematical models are developed to assess the impact of these measures on resilience. The approach is applied to an oil and gas company and found to be effective in disaster response, planning, and mitigation.
JOURNAL OF LOSS PREVENTION IN THE PROCESS INDUSTRIES
(2023)
Article
Engineering, Civil
F. Radan, S. M. T. Fatemi Ghomi, S. M. J. Mirzapour Al-e-hashem, Moeen Sammak Jalali
Summary: This paper addresses the maritime inventory routing problem (MIRP) and develops a mixed integer nonlinear programming model considering various constraints. Through studying ports in Iran and nearby areas, it is found that wind force and wave angle do not affect the routing, but only change the ship speed and costs. Tide, on the other hand, influences the route and increases costs.
TRANSPORTATION RESEARCH RECORD
(2023)
Article
Economics
Mahnaz Sohrabi, Mostafa Zandieh, Mohammad Shokouhifar
Summary: This study examines the challenges of healthcare systems in achieving sustainable inventory management of blood products. The study aims to promote social equity in healthcare provision, optimize cost management, and minimize environmental pollution. A demand-driven multi-objective inventory model is proposed, utilizing hybrid policies in an uncertain environment. The model considers different types of demands, applies a robust fuzzy stochastic programming approach, and implements a combined metaheuristic technique for solution finding. The results demonstrate the superior performance of the proposed model in minimizing costs, reducing shortages and wastage, and addressing health equity and emergencies.
SOCIO-ECONOMIC PLANNING SCIENCES
(2023)
Article
Green & Sustainable Science & Technology
Erfan Shafiee Roudbari, S. M. T. Fatemi Ghomi, Ursula Eicker
Summary: The global population growth leads to increased demand for raw materials, while governments are implementing circular economy strategies in cities and industries. This paper presents a comprehensive model of a multi-echelon closed-loop supply chain network that operates under uncertainty. The model optimizes three contradicting objectives: maximizing profit, minimizing emissions, and maximizing job creation. The augmented epsilon constraint method is applied to improve the model. Applied in the clothing industry in Montreal, Canada, the results show the attractiveness of such a network for companies seeking profit, sustainability, and entrepreneurship.
ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
(2023)
Article
Computer Science, Information Systems
Amin Rahimi, Seyed Mojtaba Hejazi, Mostafa Zandieh, Mirpouya Mirmozaffari
Summary: This paper proposes a surgical case scheduling problem that assigns n surgeries to m identical operating rooms or machines. Since optimization problems in operating rooms are NP-hard, mathematical and metaheuristic methods are used. The ordering of surgical operations in each room is a crucial part of sequencing and scheduling problems. The study introduces a no-wait open-shop surgical case scheduling problem with multi-transportation times and develops a mixed-integer linear program (MILP) to solve small-sized instances. Moreover, a hybrid simulated annealing (SA) algorithm is suggested for solving large-sized problems in an acceptable computational time.
APPLIED SYSTEM INNOVATION
(2023)
