Article
Computer Science, Interdisciplinary Applications
Shu Luo, Linxuan Zhang, Yushun Fan
Summary: This paper proposes an on-line rescheduling framework named as two-hierarchy deep Q network (THDQN) for the dynamic multi-objective flexible job shop scheduling problem with new job insertions. By optimizing two practical objectives including total weighted tardiness and average machine utilization rate, the trained THDQN has shown effectiveness and generality on a wide range of test instances.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
Binzi Xu, Yi Mei, Yan Wang, Zhicheng Ji, Mengjie Zhang
Summary: Dynamic Flexible Job Shop Scheduling (DFJSS) is a challenging problem with conflicting objectives. The traditional heuristic template may have limitations in handling dynamic environments, leading to the proposal of a novel heuristic template that delays routing decisions for improved decision accuracy. Through Genetic Programming Hyper-Heuristic (GPHH), the rules in the heuristic template are automatically evolved for better performance.
EVOLUTIONARY COMPUTATION
(2021)
Article
Engineering, Chemical
Adilanmu Sitahong, Yiping Yuan, Ming Li, Junyan Ma, Zhiyong Ba, Yongxin Lu
Summary: This study combines genetic programming with feature selection to design effective and interpretable dispatching rules for dynamic job shop scheduling. A new genetic programming method is proposed, which achieves a progressive transition from exploration to exploitation based on population diversity. The experiments show that the proposed approach outperforms other genetic programming-based algorithms in generating more interpretable and effective rules.
Article
Engineering, Industrial
Salama Shady, Toshiya Kaihara, Nobutada Fujii, Daisuke Kokuryo
Summary: Thanks to advances in computational power and machine learning algorithms, Genetic Programming (GP) can be used to automatically design scheduling rules for dynamic job shop scheduling problems. However, the computational costs and interpretability of the rules remain significant limitations. In this paper, a new representation of GP rules and an adaptive feature selection mechanism are proposed to improve solution quality by limiting the search space and generating more interpretable rules.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2022)
Article
Management
Cristiane Ferreira, Goncalo Figueira, Pedro Amorim
Summary: The emergence of Industry 4.0 is making production systems more flexible and dynamic, requiring real-time scheduling adaptation. Machine learning methods have been developed to improve scheduling rules, but they often lack interpretability and generalization. This paper proposes a novel approach that combines machine learning with domain problem reasoning to guide the empirical search for effective and interpretable dispatching rules. The experimental results show that the proposed approach outperforms existing literature in various scenarios, indicating its potential as a new paradigm for applying machine learning to dynamic optimization problems.
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2022)
Article
Engineering, Industrial
Salama Shady, Toshiya Kaihara, Nobutada Fujii, Daisuke Kokuryo
Summary: This paper proposes a feature selection approach based on the Gene Expression Programming (GEP) algorithm to evolve high-quality scheduling rules in simple structures. By restricting the search space and selecting only meaningful features, this approach can speed up the search process and generate rules with high interpretability.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Chemistry, Multidisciplinary
Adilanmu Sitahong, Yiping Yuan, Junyan Ma, Yongxin Lu, Peiyin Mo
Summary: Gene expression programming (GEP) is commonly used for creating intelligent dispatching rules in job-shop scheduling. The proper selection of terminal set is crucial for GEP success. A feature selection approach has been proposed to select the appropriate terminal set for different dynamic job-shop scenarios. The approach combines adaptive variable neighborhood search algorithm with weighted voting ranking method to obtain diverse and high-performing dispatching rules. Experimental results showed that the performance of the improved GEP algorithm with feature selection was superior to baseline dispatching rules and GEP algorithm.
APPLIED SCIENCES-BASEL
(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, Interdisciplinary Applications
M. Thenarasu, K. Rameshkumar, Jacob Rousseau, S. P. Anbuudayasankar
Summary: This study aims to solve the flexible job shop scheduling problem using discrete event simulation model, Composite Dispatching Rules (CDRs), and multi-criteria decision making (MCDM) techniques to minimize makespan, mean flow-time, mean tardiness, and maximum tardiness.
SIMULATION MODELLING PRACTICE AND THEORY
(2022)
Article
Management
Karim Tamssaouet, Stephane Dauzere-Peres
Summary: This article presents a framework that unifies and generalizes well-known literature results on local search for job-shop and flexible job-shop scheduling problems. The proposed framework focuses on quickly ruling out infeasible moves and evaluating the quality of feasible neighbors, which are crucial for the success of local search approaches. It can be applied to any scheduling problem with an appropriate defined neighborhood structure. The proposed framework introduces novel procedures for evaluating feasibility and estimating the value of objective functions for neighbor solutions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Engineering, Industrial
M. Thenarasu, K. Rameshkumar, M. Di Mascolo, S. P. Anbuudayasankar
Summary: Increased flexibility in job shops requires shop floor engineers to make more complex decisions. Partial Flexible Job Shop Scheduling (PFJSS) is a subset of job shop problems with practical applications. This study proposes a novel method integrating Multi-Criteria Decision Making (MCDM) methods and Discrete Event Simulation (DES) Model to determine job priorities in large-scale problems.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
Huali Fan, Hegen Xiong, Mark Goh
Summary: This paper introduces a mathematical programming model for dynamic job shop scheduling problem with extended technical precedence constraints (ETPC) and utilizes a constructive heuristic to solve large-scale problems. It demonstrates the effectiveness of genetic programming-based hyper-heuristic approach in generating problem-specific dispatching rules.
COMPUTERS & OPERATIONS RESEARCH
(2021)
Article
Engineering, Industrial
B. Mihoubi, B. Bouzouia, M. Gaham
Summary: The study proposes a scheduling rules-based surrogate assisted simulation-optimisation approach for solving a realistic Flexible Job Shop Scheduling Problem. The approach, applied to a highly automated Flexible robotised Manufacturing System, shows competitive performance compared to other resolution models through computational simulations and comparisons.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2021)
Article
Computer Science, Interdisciplinary Applications
Vincent Boyer, Jobish Vallikavungal, Xavier Cantu Rodriguez, M. Angelica Salazar-Aguilar
Summary: This study introduces a generalized flexible job-shop scheduling problem with additional hard constraints, inspired by a real manufacturing situation. Mathematical models and a metaheuristic algorithm are proposed to address the problem, with experimental results showing the effectiveness of the algorithm in handling large instances.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
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
Engineering, Manufacturing
Zeynep Idil Erzurum Cicek, Zehra Kamisli Ozturk
Summary: This study investigates the applicability of one-class classification models in traffic accident prediction and finds that the one-class SVM model outperforms binary classification models, with alarm rates confirming the suitability of OCC for accident prediction.
INTERNATIONAL JOURNAL OF CRASHWORTHINESS
(2022)
Article
Computer Science, Interdisciplinary Applications
Halil Ibrahim Ayaz, Zehra Kamisli Ozturk
Summary: Railways are becoming increasingly important in transportation, with a focus on developing algorithms to solve train seat scheduling problems. A mathematical model and a heuristic algorithm have been proposed to address these issues effectively.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Genetics & Heredity
Selcuk Ozdemir, Nurhak Aksungur, Necip Altundas, Salih Kara, Ercan Korkut, Mustafa Ozkaraca, Ali Sefa Mendil, Gurkan Ozturk
Summary: This study investigated the potential of serum-derived exosomal circRNAs in the diagnosis of hepatic alveolar echinococcosis. High-throughput sequencing was used to detect circRNAs related to the disease, followed by bioinformatic and pathway analyzes. The validation results suggest that the identified exosomal circRNAs could serve as biomarkers for hepatic alveolar echinococcosis detection.
Article
Computer Science, Software Engineering
Erdener Ozcetin, Gurkan Ozturk
Summary: This study discusses the Open Vehicle Routing Problem commonly used by companies with third-party logistics services, which belongs to the class of high-dimensional and complex optimization problems. A three-phase Variable Neighborhood Search Algorithm is proposed to efficiently solve large-scale problems. The algorithm utilizes eight different neighborhoods and employs wise shaking strategies to overcome local optimal solutions. The method's competitiveness is tested on literature test instances and comparatively evaluated.
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
(2023)
Article
Computer Science, Interdisciplinary Applications
Aydin Teymourifar
Summary: This study proposes a new model based on the concept of resectorization to balance the accessibility of healthcare services. By defining a new bi-objective function and using simulation-based optimization and contract mechanisms, it is achievable to achieve the balance of healthcare units' accessibility.
JOURNAL OF SIMULATION
(2022)
Article
Green & Sustainable Science & Technology
Aydin Teymourifar, Maria A. M. Trindade
Summary: This study proposes a framework for designing green contracting mechanisms in forestry supply chain management to integrate sustainable goals into business objectives. The framework considers the interests of different parties and uses multi-attribute decision-making techniques to evaluate scenarios for more interpretable results. It can assist businesses in designing contracts that promote sustainability and comply with the United Nations' Sustainable Development Goals.
Article
Green & Sustainable Science & Technology
Aydin Teymourifar, Maria A. M. Trindade
Summary: In this paper, the authors propose a novel approach to the development of green public policies, emphasizing the significance of the system of systems (SoSs) methodology. They use decision-making trial and evaluation laboratory (DEMATEL) and interpretive structural modeling (ISM) techniques to understand the relationships between different systems and provide a literature review on the application of these techniques.
Article
Multidisciplinary Sciences
Aydin Teymourifar
Summary: This study compares the performance of optimization software in solving the bi-objective sectorization problem. The approach used transforms the bi-objective model into single-objective ones and solves them using ideal and anti-ideal points. The results show that GAMS software performs the best in solving the models, while metaheuristics from the Pymoo library obtain feasible results in reasonable times.
Review
Medicine, General & Internal
Fahri Aydin, Ahmet Yalcin, Adem Karaman, Recep Sade, Gurkan Ozturk, Fatih Alper
Summary: Alveolar echinococcosis is a life-threatening zoonotic disease primarily involving the liver and showing tumor-like growth. Early diagnosis is difficult, but can be achieved through medical history, radiological imaging, and serological and histopathological tests. Radiological imaging methods are crucial for early and differential diagnosis.
EURASIAN JOURNAL OF MEDICINE
(2022)
Article
Medicine, General & Internal
Salih Kara, Ercan Korkut, Nurhak Aksungur, Necip Altundas, Gurkan Ozturk, Zuhal Yetis Demir
Summary: This study compared the effects of two arterial anastomosis techniques on the outcome of kidney transplantation. The results showed no significant difference in creatinine levels and urine volume between the two surgical techniques. Only the urine volume on the 7th day after surgery had a significant effect on graft survival. There was no significant difference in graft survival between the two anastomosis techniques.
JCPSP-JOURNAL OF THE COLLEGE OF PHYSICIANS AND SURGEONS PAKISTAN
(2022)
Article
Medicine, General & Internal
Ercan Korkut, Nurhak Aksungur, Necip Altundas, Salih Kara, Rifat Peksoez, Gurkan Ozturk
Summary: This study retrospectively evaluated the outcomes of treating giant incisional hernia using open intraperitoneal dual mesh. The results showed that this method is an effective treatment option with low complication and recurrence rates.
CUREUS JOURNAL OF MEDICAL SCIENCE
(2022)
Article
Medicine, General & Internal
Ercan Korkut, Nurhak Aksungur, Necip Altundas, Salih Kara, Rifat Peksoz, Mesud Fakirullahoglu, Gurkan Ozturk
Summary: The study aimed to compare the parameters influencing patient selection, cyst features, treatment outcomes, morbidity, and death rates between open and laparoscopic surgery for hepatic hydatid disease. The results showed that laparoscopic surgery was an effective and safe intervention for cysts in the accessible peripheral segments of the liver.
ANNALS OF CLINICAL AND ANALYTICAL MEDICINE
(2022)
Article
Medicine, General & Internal
Ercan Korkut, Nurhak Aksungur, Gurkan Ozturk
Summary: This study aimed to compare the treatment outcomes and factors influencing the choice between spleen-preserving cystotomy and splenectomy in patients with splenic cystic echinococcosis. The results showed no complications, re-operation requirements, or recurrence during the follow-up period, suggesting the use of spleen-preserving cystotomy.
EURASIAN JOURNAL OF MEDICINE
(2022)
Proceedings Paper
Engineering, Industrial
Aydin Teymourifar, Ana Maria Rodrigues, Jose Soeiro Ferreira, Cristina Lopes, Cristina Oliveira, Valeria Romanciuc
Summary: This paper proposes a new two-stage solution method for solving multi-objective location-routing problems. It assigns customers to distribution centres using the concept of sectorization and determines routes for each sector to meet customer demands. The effectiveness of this method is demonstrated by comparing the results with those obtained using NSGA-II.
INNOVATIONS IN INDUSTRIAL ENGINEERING
(2022)
Proceedings Paper
Engineering, Industrial
Valeria Romanciuc, Cristina Lopes, Aydin Teymourifar, Ana Maria Rodrigues, Jose Soeiro Ferreira, Cristina Oliveira, Elif Goksu Ozturk
Summary: The process of sectorization involves dividing a dataset into smaller sectors based on specific criteria. This paper proposes two quadratic integer programming models for sectorization, one focusing on compactness with equilibrium constraints, and the other considering equilibrium as the objective with compactness bounded in the constraints. The relationship between the criteria is also compared.
INNOVATIONS IN INDUSTRIAL ENGINEERING
(2022)
