Article
Engineering, Industrial
Hugo Hissashi Miyata, Marcelo Seido Nagano
Summary: Nowadays, distributed scheduling problem is a reality in many companies. Over the last years, an increasingly attention has been given to the distributed flow shop scheduling problem and the addition of constraints to the problem. This article introduces a new distributed no-wait flow shop scheduling problem using a mix of mixed-integer linear programming and heuristic algorithms. Studies show that the proposed algorithm performs well in the trade-off between efficiency and effectiveness.
JOURNAL OF MANUFACTURING SYSTEMS
(2021)
Article
Computer Science, Interdisciplinary Applications
Karam Allali, Said Aqil, Jabrane Belabid
Summary: This paper investigates a multi-objective optimization distributed no-wait permutation flow shop scheduling problem under the constraint of sequence dependent setup time. The study proposes mixed integer linear programming and several efficient metaheuristics to solve this industrial problem. The combination of the genetic algorithm and Nawaz-Enscore-Ham algorithm yields the best results.
SIMULATION MODELLING PRACTICE AND THEORY
(2022)
Article
Operations Research & Management Science
Fernando Siqueira de Almeida, Marcelo Seido Nagano
Summary: In this article, the m-machine no-wait flow shop scheduling problem with sequence dependent setup times is addressed. A new heuristic called I G(A) is developed to solve the problem by repeatedly performing a process of destruction and construction of an existing solution. Computational experiments show that I G(A) outperforms the best literature method for similar applications in overall solution quality by about 35%. Therefore, IG(A) is recommended to solve the problem.
4OR-A QUARTERLY JOURNAL OF OPERATIONS RESEARCH
(2023)
Article
Engineering, Industrial
Christos Koulamas, George J. Kyparisis
Summary: The study focuses on the no-wait flow shop scheduling problem with a rejection option and presents polynomial-time algorithms to minimize different objective functions efficiently.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2021)
Article
Computer Science, Artificial Intelligence
Victor M. Valenzuela-Alcaraz, M. A. Cosio-Leon, A. Danisa Romero-Ocano, Carlos A. Brizuela
Summary: The study proposes a cooperative coevolutionary algorithm for solving the no-wait job shop scheduling problem. The algorithm evolves permutations and binary chains simultaneously to optimize sequencing and timetabling decisions, and includes one-step perturbation mechanisms to improve solution quality. Experimental results show that the proposed algorithm produces competitive results and obtains new best values for some instances.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Computer Science, Interdisciplinary Applications
Weishi Shao, Zhongshi Shao, Dechang Pi
Summary: This paper investigates a distributed no-wait flexible flow shop scheduling problem with makespan criterion, presenting a mixed-integer linear programming model and machine selection method, as well as developing greedy factory assignment rules and dispatch rules. Multiple constructive heuristics are obtained by combining different rules, and a variable neighborhood descend constructive heuristic version is designed to tackle the problem.
COMPUTERS & OPERATIONS RESEARCH
(2021)
Article
Computer Science, Interdisciplinary Applications
Hugo Hissashi Miyata, Marcelo Seido Nagano
Summary: This article introduces a distributed blocking flow shop scheduling problem with sequence-dependent setup times and maintenance operations, and proposes an iterative greedy method to solve this problem. Computational experiments demonstrate that the proposed method achieves a good balance between effectiveness and efficiency.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
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
Management
Fernando Siqueira de Almeida, Marcelo Seido Nagano
Summary: This paper proposes four algorithms for the no-wait flow shop scheduling problem, addressing the problem with sequence-dependent setup times. The algorithms improve the incumbent solution through a process of destruction and repair, exploring search intensification-diversification at different levels. Computational experiments demonstrate that the best proposed algorithm significantly outperforms existing methods.
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
(2023)
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
Computer Science, Artificial Intelligence
Qing-qing Zeng, Jun-qing Li, Rong-hao Li, Ti-hao Huang, Yu-yan Han, Hong-yan Sang
Summary: This paper addresses a multi-objective energy-efficient scheduling problem of the distributed permutation flowshop with sequence-dependent setup time and no-wait constraints. It proposes a new mixed-integer linear programming model and an improved non-dominated sorting genetic algorithm, along with problem-specific heuristics and search operators, to enhance the algorithm performance.
COMPLEX & INTELLIGENT SYSTEMS
(2023)
Article
Computer Science, Interdisciplinary Applications
Abdennour Azerine, Mourad Boudhar, Djamal Rebaine
Summary: This paper investigates the two-machine no-wait flow shop scheduling problem with two competing agents, proposing exact and approximation algorithms, mathematical programming model, and conducting experiments to demonstrate their effectiveness.
JOURNAL OF COMBINATORIAL OPTIMIZATION
(2022)
Article
Automation & Control Systems
Bin Qian, Zi-Qi Zhang, Rong Hu, Huai-Ping Jin, Jian-Bo Yang
Summary: In this article, a matrix-cube-based estimation of distribution algorithm is proposed to solve the no-wait flow-shop scheduling problem with sequence-dependent setup times and release times. The algorithm demonstrates efficient exploration and exploitation in the solution space, leading to improved solutions compared to state-of-the-art algorithms.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Engineering, Industrial
Imma Ribas, Ramon Companys
Summary: This paper addresses the scheduling problem in a parallel flow shop environment without buffers between machines and with sequence-dependent setup times to minimize the maximum completion time of jobs. 36 heuristics were tested, with one designed specifically for considerable setup times showing good performance. A combined heuristic approach was also proposed for finding good solutions in a short CPU time.
INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING COMPUTATIONS
(2021)
Article
Computer Science, Interdisciplinary Applications
Francisco Angel-Bello, Jobish Vallikavungal, Ada Alvarez
Summary: This paper investigates the makespan minimization in a dynamic single-machine scheduling problem with sequence-dependent setup times, and proposes two rescheduling strategies with corresponding algorithms. Experimental results show that these algorithms are fast and provide high-quality solutions.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
Mohamed M. S. Abdulkader, Yuvraj Gajpal, Tarek Y. ElMekkawy
APPLIED SOFT COMPUTING
(2015)
Article
Computer Science, Artificial Intelligence
Alireza Saremi, Payman Jula, Tarek ElMekkawy, Gary G. Wang
EXPERT SYSTEMS WITH APPLICATIONS
(2015)
Article
Engineering, Industrial
Andrei Sleptchenko, Hasan Huseyin Turan, Shaligram Pokharel, Tarek Y. ElMekkawy
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2019)
Article
Engineering, Industrial
M. M. S. Abdulkader, Yuvraj Gajpal, Tarek Y. ElMekkawy
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2018)
Article
Computer Science, Interdisciplinary Applications
Hasan Huseyin Turan, Andrei Sleptchenko, Shaligram Pokharel, Tarek Y. ElMekkawy
COMPUTERS & INDUSTRIAL ENGINEERING
(2018)
Article
Computer Science, Interdisciplinary Applications
Hasan Huseyin Turan, Andrei Sleptchenko, Shaligram Pokharel, Tarek Y. ElMekkawy
COMPUTERS & OPERATIONS RESEARCH
(2020)
Article
Construction & Building Technology
Md. Anisul Islam, Yuvraj Gajpal, Tarek Y. ElMekkawy
Summary: Sustainable transportation is essential for minimizing global CO2 emissions. This paper introduces a mixed fleet based green clustered logistics problem and proposes a new hybrid metaheuristic algorithm to solve it, which outperforms state-of-the-art algorithms in extensive computational experiments.
SUSTAINABLE CITIES AND SOCIETY
(2021)
Article
Chemistry, Multidisciplinary
Omar Jouma El-Hafez, Tarek Y. ElMekkawy, Mohamed Bin Mokhtar Kharbeche, Ahmed Mohammed Massoud
Summary: Over the past few decades, there has been significant progress in reducing the cost of photovoltaic (PV) energy. Large PV systems are now being connected to the electricity grid to provide power during the day. However, transmitting and distributing this electricity through the grid results in power losses. Therefore, it is important to have an optimal energy allocation between conventional power plants and large-scale PV power plants to minimize costs. This paper presents a generic model for economic energy allocation that takes into account operational aspects and contractual provisions. The model can be used in the design or operation phases to minimize operating costs and can be applied to any country or electricity system.
APPLIED SCIENCES-BASEL
(2022)
Article
Energy & Fuels
Rabah Ismaen, Tarek Y. ElMekkawy, Shaligram Pokharel, Adel Elomri, Mohammed Al-Salem
Summary: This paper analyzes the potential of integrating solar energy with cooling systems in the Middle East, and evaluates and compares different configurations in terms of economic, renewable energy use, and environmental performance. The results show that the competitiveness of solar energy integration is influenced by electricity tariff and available installation area. Among the solar assisted cooling systems, the PV-DCS configuration is economically competitive, while the PVT-DCS configuration has the lowest operation cost and highest environmental performance.
Article
Thermodynamics
Rabah Ismaen, Tarek Y. El Mekkawy, Shaligram Pokharel, Mohammed Al-Salem
Summary: This paper discusses the importance of district cooling systems in the Middle East and proposes an analysis framework that considers system and stakeholders' requirements. The framework utilizes a mathematical model to optimize the system cost and improve energy efficiency.
Article
Green & Sustainable Science & Technology
Omar Jouma El-Hafez, Tarek Y. ElMekkawy, Mohamed Kharbeche, Ahmed Massoud
Summary: The COVID-19 pandemic has affected Qatar's electricity demand and forecasting, with student and employee attendance being the most influential restriction on electricity demand, leading to a nearly 28% increase in domestic peak demand due to student attendance. Historical data and statistical analysis were used to assess the impact of the pandemic on electricity demand in Qatar.
Review
Environmental Sciences
Hesham Ali Behary Aboelkhir, Adel Elomri, Tarek Y. ElMekkawy, Laoucine Kerbache, Mohamed S. Elakkad, Abdulla Al-Ansari, Omar M. Aboumarzouk, Abdelfatteh El Omri
Summary: This study conducted a systematic literature review to understand the current methods and future directions in improving the referral process. It found a lack of attention to the primary referral of blood cancer cases and highlighted the need for more research to optimize the referral process, particularly for suspected hematological cancer patients.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
(2022)
Article
Operations Research & Management Science
Arshad Ali, Yuvraj Gajpal, Tarek Y. Elmekkawy
Summary: This paper examines the distributed permutation flowshop scheduling problem (DPFSP) and proposes a metaheuristic approach, tabu search (TS), to solve the problem. Experimental results show that tabu search outperforms existing metaheuristics in terms of solution quality.
Article
Multidisciplinary Sciences
Dana Alghool, Tarek Elmekkawy, Mohamed Haouari, Adel Elomri
Proceedings Paper
Computer Science, Artificial Intelligence
Andrei Sleptchenko, Tarek Elmekkawy, Hasan Huseyin Turan, Shaligram Pokharel
2017 NINTH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTATIONAL INTELLIGENCE (ICACI)
(2017)
