Article
Computer Science, Artificial Intelligence
Ming Li, Bin Su, Deming Lei
Summary: The paper considers the fuzzy distributed assembly flow shop scheduling problem and proposes an algorithm optimized through imperialist cooperation. Experimental results demonstrate the excellent performance of the algorithm in solving the problem.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2021)
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, Artificial Intelligence
Xin-rui Tao, Jun-qing Li, Ti-hao Huang, Peng Duan
Summary: The research on resource-constrained hybrid flowshop problem led to the proposal of a discrete imperialist competitive algorithm (DICA) to minimize makespan and energy consumption. The algorithm represents solutions using two-dimensional vectors, with one for scheduling sequence and the other for machine assignment, and incorporates a decoding method considering resource allocation. By combining DICA with simulated annealing algorithm (SA), the proposed approach showed high efficiency in solving the RCHFS problem.
COMPLEX & INTELLIGENT SYSTEMS
(2021)
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
Engineering, Industrial
Biao Han, Quan-Ke Pan, Liang Gao
Summary: This paper addresses a serial distributed permutation flowshop scheduling problem (SDPFSP) inspired by a printed circuit board assembly process. A cooperative iterated greedy (CIG) algorithm is developed to optimize the solution. Problem-specific operators and computational experiments are conducted to verify the effectiveness of the proposed algorithm and its superiority over existing methods.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Deming Lei, Haoyang Du, Hongtao Tang
Summary: This study focuses on DAFSP with Pm -> 1 layout and transportation time, and proposes an imperialist competitive algorithm with cooperation and division (CDICA) to minimize makespan. A heuristic is applied to generate initial solutions based on problem features. Adaptive cooperation and evolution are performed in the imperialist competition process, and empire division is carried out under certain conditions. Experimental results demonstrate the effectiveness of the new strategies, and CDICA proves to be highly competitive in solving the considered DAFSP.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2023)
Article
Engineering, Multidisciplinary
Marcelo Seido Nagano, Fernando Siqueira de Almeida, Hugo Hissashi Miyata
Summary: This article proposes an iterated greedy-with-local-search algorithm for the no-wait flowshop scheduling problem, which outperforms both the mathematical model and the best existing algorithm in terms of effectiveness and efficiency according to computational experiments and statistical analysis.
ENGINEERING OPTIMIZATION
(2021)
Article
Operations Research & Management Science
Pourya Pourhejazy, Chen-Yang Cheng, Kuo-Ching Ying, Nguyen Hoai Nam
Summary: This study extends the integrated scheduling of distributed manufacturing operations and proposes a new mathematical model and algorithm to solve the distributed two-stage assembly flowshop scheduling problem. Experimental results demonstrate that the proposed algorithm significantly outperforms the current best algorithm in terms of performance.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Operations Research & Management Science
Ali Allahverdi, Muberra Allahverdi
Summary: In this study, we address the problem of scheduling three machines in a flowshop environment with uncertain processing times. Sixteen algorithms based on Johnson's algorithm are proposed, and computational experiments are conducted using randomly generated data. The results show that algorithm AL-7 outperforms the others significantly. Hypothesis tests confirm the statistical significance of the findings. In algorithm AL-7, more weight is given to the processing times of jobs on the first and third machines compared to the second machine. Both the lower and upper bounds of job processing times on all machines are utilized. Algorithm AL-7 performs the best regardless of the extreme distributions considered, making it the recommended choice.
RAIRO-OPERATIONS RESEARCH
(2023)
Article
Management
Xiaojuan Jiang, Kangbok Lee, Michael L. Pinedo
Summary: This paper considers bicriteria scheduling problems with identical machines, involving conflicting objectives of makespan and total completion time. The authors propose a fast approximation algorithm and analyze the problem's inapproximability.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Carla Talens, Victor Fernandez-Viagas, Paz Perez-Gonzalez, Antonio Costa
Summary: This paper addresses the 2-stage assembly scheduling problem aiming to minimize makespan with availability constraints. Novel constructive and composite heuristics are proposed, which outperform existing methods in computational evaluations.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Computer Science, Artificial Intelligence
Chen-Yang Cheng, Pourya Pourhejazy, Kuo-Ching Ying, Shi-Yao Huang
Summary: This study developed an effective metaheuristic to address Blocking Flowshop Scheduling Problems with Sequence-Dependent Setup-Times, showing superior performance and potential applications in solving other complex scheduling problems.
APPLIED SOFT COMPUTING
(2021)
Article
Computer Science, Interdisciplinary Applications
A. Baskar, M. Anthony Xavior
Summary: This paper introduces three simple idle times based tie-breaking mechanisms for permutation flowshop scheduling problems, and compares the performance with popular tie-breaking mechanisms using Taillard and Vallada-Framinan-Ruiz benchmark problems. The computational results show that the proposed tie-breaker performs comparably with many top-performing tie-breaking mechanisms, while keeping the computation time unchanged.
COMPUTERS & OPERATIONS RESEARCH
(2021)
Article
Automation & Control Systems
Yuan-Zhen Li, Kaizhou Gao, Lei-Lei Meng, Ponnuthurai Nagaratnam Suganthan
Summary: This work addresses the distributed permutation flowshop scheduling problem (DPFSP) with peak power consumption. An improved artificial bee colony (IABC) algorithm is proposed to solve the problem, utilizing new solution generation operators and a local search operation. Experimental results show that the IABC algorithm performs well in solving the DPFSP with peak power consumption.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
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
Operations Research & Management Science
Seyed Shamsodin Hosseini, Parham Azimi, Mani Sharifi, Mostafa Zandieh
Summary: This paper addresses the dynamic facility layout problem by proposing a new mathematical model to simultaneously determine the best machine positions and plan transportation operations. A hybrid meta-heuristic approach, combining modified genetic algorithm and cloud-based simulated annealing algorithm, is developed to solve the model effectively. The proposed methodology is compared with two meta-heuristics on a set of test problems.
RAIRO-OPERATIONS RESEARCH
(2021)
Article
Operations Research & Management Science
Nassibeh Janatyan, Mostafa Zandieh, Akbar Alem-Tabriz, Masood Rabieh
Summary: The study addresses uncertainties and sustainability in pharmaceutical distribution networks using a new model and optimal algorithms, improving environmental, social, and economic conditions. Adjusting algorithm parameters, the MOPSO algorithm demonstrated the best performance in achieving optimal Pareto approximation.
ANNALS OF OPERATIONS RESEARCH
(2021)
Article
Automation & Control Systems
Ashkan Ayough, Farbod Farhadi, Mostafa Zandieh
Summary: This paper explores the role of job rotation in lean manufacturing, proposing an optimization model that considers human behavior parameters and conducting sensitivity analysis of input parameters. The findings suggest that job rotation schedules and human cognitive metrics impact the performance of lean manufacturing, and general rules are derived. Additionally, the authors use response surface methodology for experimental design, revealing important information about the impact of job rotations on operator performance and the overall working cell.
ASSEMBLY AUTOMATION
(2021)
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
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
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, Industrial
Farzaneh Nazarizadeh, Akbar Alemtabriz, Mostafa Zandieh, Abbas Raad
Summary: This paper proposes an analytical model to estimate the dependent failure rate for the Iranian railway system, aiming to accurately assess and predict the reliability of the whole system by considering both common cause failure and interactive failure. The model uses a two-variable Taylor expansion approach to estimate the dependent failure rate and determines the coefficients by expert estimation method. The research results show an improvement in the accuracy of reliability prediction compared to other models.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2022)
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
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)
Article
Engineering, Multidisciplinary
H. Jafar-Zanjani, M. Zandieh, M. Khalilzadeh
Summary: This study focuses on scheduling periodic services for customers in different locations with different service needs, presenting a novel mixed integer linear programming model with augmented epsilon constraint method. Additionally, a bi-objective meta-heuristic technique based on genetic algorithm is proposed for solving large-scale problems.
Article
Engineering, Multidisciplinary
Ashkan Ayough, Farbod Farhadi, Mostafa Zandieh, Parisa Rastkhadiv
Summary: This paper presents a metaheuristic approach to solve a customer priority based location-allocation problem, considering obstacles and location-dependent supplier capacities in network design. The computational findings show that the best allocation strategies derived from the proposed algorithms can effectively address issues in disaster relief and healthcare management.
JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION
(2021)
Article
Medical Informatics
Mahnaz Sohrabi, Mostafa Zandieh, Behrouz Afshar Nadjafi
Summary: This paper introduces a reference data model for blood bank management to address uncertainties and constraints in inventory control. It utilizes optimization concepts to reduce waste and shortages, providing real-time insights for decision-making. The model is designed to meet user requirements and support inventory information and logistic planning systems.
HEALTHCARE INFORMATICS RESEARCH
(2021)
