Article
Management
T. van der Beek, D. Souravlias, J. T. van Essen, J. Pruyn, K. Aardal
Summary: The resource constrained project scheduling problem is a complex issue. We introduce the concept of group graphs and propose a solution using a hybrid differential evolution algorithm, which has shown to be effective in practical applications.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Construction & Building Technology
Zhengming Hua, Zhenyuan Liu, Lijing Yang, Liu Yang
Summary: In this paper, an improved genetic algorithm based on time window decomposition is proposed to solve the resource-constrained project scheduling problem (RCPSP). The experimental results show that the proposed approach is competitive in solving real-life cases and provides useful insights for future research on RCPSP using other evolutionary algorithms.
AUTOMATION IN CONSTRUCTION
(2022)
Article
Management
Dries Bredael, Mario Vanhoucke
Summary: This paper provides a review of ten existing metaheuristic solution procedures for the resource-constrained multi-project scheduling problem. Algorithmic implementations are constructed and verified on original test instances. An extensive benchmark analysis is performed on a novel dataset, resulting in an overall ranking of the metaheuristic solution methods and key insights into competitive solutions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
Zhiqiang Ma, Weibo Zheng, Zhengwen He, Nengmin Wang, Xuejun Hu
Summary: This paper investigates the proactive resource-constrained project scheduling problem with resource transfer times, proposes a novel robust project scheduling model, and solves it using a genetic algorithm. Experimental results show that considering breakable flows and local search in the decoding process does not significantly improve schedule robustness, but increases computational time.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Computer Science, Software Engineering
Furkan Uysal, Rifat Sonmez, Selcuk Kursat Isleyen
Summary: The article presents a parallel GPU-based genetic algorithm for solving the resource-constrained multi-project scheduling problem. It aims to find start times for activities in order to minimize portfolio duration while satisfying constraints, showing high potential for improving performance in large-scale problems.
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
(2021)
Article
Mathematics
Ran Etgar, Yuval Cohen
Summary: The process of project portfolio selection is crucial, especially for R&D organizations. This research provides a novel heuristic method for allocating limited resources over multi-year planning horizons and compares its results with other methods. It culminates with an efficient tool that can provide practical and academic benefits.
Article
Computer Science, Interdisciplinary Applications
Ece Yagmur, Saadettin Erhan Kesen
Summary: The study investigates a joint production scheduling and outbound distribution planning problem, using a mixed integer programming formulation and genetic algorithm to reduce delivery delays and vehicle travel time, proposing a new splitting procedure. Experimental results indicate that genetic algorithm outperforms simulated annealing in terms of solution quality for medium and large instances.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Computer Science, Theory & Methods
Jun Suk Kim, Chang Wook Ahn
Summary: Quantum genetic algorithm is a research field to discover a potential structure for effective heuristic evolutionary optimization powered by quantum computation. This paper proposes an improvement by reducing randomness to decrease the population size and alleviate computational inefficiency issues of the algorithm.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2022)
Article
Computer Science, Information Systems
Natasha Nigar, Muhammad Kashif Shahzad, Shahid Islam, Olukayode Oki, Jose Manappattukunnel Lukose
Summary: This research presents a novel approach to deal with the dynamic event of 'new employee addition' in software project scheduling. It models the problem as a multi-objective optimization and utilizes domain knowledge to generate a robust schedule.
Article
Computer Science, Information Systems
Firoz Mahmud, Forhad Zaman, Ali Ahrari, Ruhul Sarker, Daryl Essam
Summary: This paper proposes a customized evolutionary algorithm integrated with three heuristics to tackle the resource-constrained project scheduling problem with singular activities. Testing on a wide range of benchmark problems reveals that the proposed approach outperforms existing algorithms.
Article
Computer Science, Artificial Intelligence
Eduardo Tadeu Bacalhau, Luciana Casacio, Anibal Tavares de Azevedo
Summary: The study focuses on the berth allocation problem (BAP) and develops a dynamic model with a novel combination of genetic algorithm and an approximated dynamic programming for local search. Through case studies and computational experiments, the metaheuristics are shown to handle large instances and tight schedules in busy port systems effectively.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Information Systems
Xuewen Xia, Huixian Qiu, Xing Xu, Yinglong Zhang
Summary: In this paper, a multi-objective genetic algorithm (MOGA) is proposed and applied to optimize workflow scheduling problems under the cloud computing environment. An initialization scheduling sequence scheme is introduced to enhance search efficiency, and the longest common subsequence (LCS) is integrated into the genetic algorithm (GA) to achieve a balance between exploration and exploitation. Experimental results demonstrate that the proposed GALCS algorithm outperforms ordinary GA and other state-of-the-art algorithms in finding a better Pareto front.
INFORMATION SCIENCES
(2022)
Article
Chemistry, Multidisciplinary
Pornpote Nusen, Wanarut Boonyung, Sunita Nusen, Kriengsak Panuwatwanich, Paskorn Champrasert, Manop Kaewmoracharoen
Summary: This study focuses on utilizing a multi-objective genetic algorithm for building information modeling, aiming to improve construction planning and resource management through the combination of BIM and MOGA. By using the BIM-MOGA tool, optimal results in terms of total cost, time usage, and resource allocation can be achieved in renovation projects.
APPLIED SCIENCES-BASEL
(2021)
Article
Computer Science, Artificial Intelligence
Md Asadujjaman, Humyun Fuad Rahman, Ripon K. Chakrabortty, Michael J. Ryan
Summary: This study proposes a multi-operator immune genetic algorithm (MO-IGA) to solve the resource constrained project scheduling problem with discounted cash flows (RCPSPDC). The MO-IGA integrates a genetic algorithm and an immune algorithm, and utilizes dynamic operators and local search strategies to optimize the solution quality. Experimental results demonstrate the superiority of the proposed MO-IGA over other methods in terms of performance metrics.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Mathematics
Chen-Yang Cheng, Shih-Wei Lin, Pourya Pourhejazy, Kuo-Ching Ying, Yu-Zhe Lin
Summary: The production environment in modern industries features zero idle-time between jobs on each machine, improving energy efficiency and impacting cleaner production in other scenarios. This study developed an extended solution for optimizing the Bi-objective No-Idle Permutation Flowshop Scheduling Problem (BNIPFSP) after conducting a comprehensive literature review. Extensive numerical tests and statistical analysis revealed that the proposed extension outperformed in terms of solution quality, although at the expense of longer computational time.
Article
Management
Jose Fernando Goncalves, Mauricio G. C. Resende
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2015)
Article
Transportation Science & Technology
A. Galrao Ramos, Jose F. Oliveira, Jose F. Goncalves, Manuel P. Lopes
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2015)
Editorial Material
Management
A. Miguel Gomes, Jose Fernando Goncalves, Ramon Alvarez-Valdes, J. Valerio de Carvalho
International Transactions in Operational Research
(2016)
Article
Economics
A. Galrao Ramos, Jose F. Oliveira, Jose F. Goncalves, Manuel P. Lopes
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2016)
Article
Computer Science, Interdisciplinary Applications
Antonio Augusto Chaves, Jose Fernando Goncalves, Luiz Antonio Nogueira Lorena
COMPUTERS & INDUSTRIAL ENGINEERING
(2018)
Article
Engineering, Industrial
Jose Fernando Goncalves, Mauricio G. C. Resende
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2013)
Article
Operations Research & Management Science
Dalila B. M. M. Fontes, Jose Fernando Goncalves
OPTIMIZATION LETTERS
(2013)
Article
Operations Research & Management Science
Ricardo M. A. Silva, Diego M. Silva, Mauricio G. C. Resende, Geraldo R. Mateus, Jose F. Goncalves, Paola Festa
OPTIMIZATION LETTERS
(2014)
Editorial Material
Management
A. Miguel Gomes, Jose Fernando Goncalves, Ramon Alvarez-Valdes, Valerio de Carvalho
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH
(2013)
Article
Management
Jose Fernando Goncalves, Mauricio G. C. Resende
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH
(2014)
Article
Management
Jose Fernando Goncalves, Mauricio G. C. Resende, Miguel Dias Costa
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH
(2016)
Article
Management
Jose Fernando Goncalves, Gerhard Waescher
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2020)
Proceedings Paper
Automation & Control Systems
Jose Fernando Goncalves
Proceedings Paper
Operations Research & Management Science
Dalila B. M. M. Fontes, Jose Fernando Goncalves
OPTIMIZATION, CONTROL, AND APPLICATIONS IN THE INFORMATION AGE: IN HONOR OF PANOS M. PARDALOS'S 60TH BIRTHDAY
(2015)
Article
Engineering, Electrical & Electronic
Dalila B. M. M. Fontes, Jose Fernando Goncalves, Fernando A. C. C. Fontes
RECENT ADVANCES IN ELECTRICAL & ELECTRONIC ENGINEERING
(2018)
Review
Management
Vinicius N. Motta, Miguel F. Anjos, Michel Gendreau
Summary: This survey presents a review of optimization approaches for the integration of demand response in power systems planning and highlights important future research directions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Philipp Schulze, Armin Scholl, Rico Walter
Summary: This paper proposes an improved branch-and-bound algorithm, R-SALSA, for solving the simple assembly line balancing problem, which performs well in balancing workloads and providing initial solutions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Roshan Mahes, Michel Mandjes, Marko Boon, Peter Taylor
Summary: This paper discusses appointment scheduling and presents a phase-type-based approach to handle variations in service times. Numerical experiments with dynamic scheduling demonstrate the benefits of rescheduling.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Oleg S. Pianykh, Sebastian Perez, Chengzhao Richard Zhang
Summary: Efficient scheduling is crucial for optimizing resource allocation and system performance. This study focuses on critical utilization and efficient scheduling in discrete scheduling systems, and compares the results with classical queueing theory.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Review
Management
Hamed Jahani, Babak Abbasi, Jiuh-Biing Sheu, Walid Klibi
Summary: Supply chain network design is a large and growing area of research. This study comprehensively surveys and analyzes articles published from 2008 to 2021 to detect and report financial perspectives in SCND models. The study also identifies research gaps and offers future research directions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Patrick Healy, Nicolas Jozefowiez, Pierre Laroche, Franc Marchetti, Sebastien Martin, Zsuzsanna Roka
Summary: The Connected Max-k-Cut Problem is an extension of the well-known Max-Cut Problem, where the objective is to partition a graph into k connected subgraphs by maximizing the cost of inter-partition edges. The researchers propose a new integer linear program and a branch-and-cut algorithm for this problem, and also use graph isomorphism to structure the instances and facilitate their resolution. Extensive computational experiments show that, if k > 2, their approach outperforms existing algorithms in terms of quality.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Victor J. Espana, Juan Aparicio, Xavier Barber, Miriam Esteve
Summary: This paper introduces a new methodology based on the machine learning technique MARS for estimating production functions that satisfy classical production theory axioms. The new approach overcomes the overfitting problem of DEA through generalized cross-validation and demonstrates better performance in reducing mean squared error and bias compared to DEA and C2NLS methods.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Stefano Nasini, Rabia Nessah
Summary: In this paper, the authors investigate the impact of time flexibility in job scheduling, showing that it can significantly affect operators' ability to solve the problem efficiently. They propose a new methodology based on convex quadratic programming approaches that allows for optimal solutions in large-scale instances.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Zhiqiang Liao, Sheng Dai, Timo Kuosmanen
Summary: Nonparametric regression subject to convexity or concavity constraints is gaining popularity in various fields. The conventional convex regression method often suffers from overfitting and outliers. This paper proposes the convex support vector regression method to address these issues and demonstrates its advantages in prediction accuracy and robustness through numerical experiments.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Kuo-Hao Chang, Ying-Zheng Wu, Wen-Ray Su, Lee-Yaw Lin
Summary: The damage and destruction caused by earthquakes necessitates the evacuation of affected populations. Simulation models, such as the Stochastic Pedestrian Cell Transmission Model (SPCTM), can be utilized to enhance disaster and evacuation management. The analysis of SPCTM provides insights for government officials to formulate effective evacuation strategies.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Qinghua Wu, Mu He, Jin-Kao Hao, Yongliang Lu
Summary: This paper studies a variant of the orienteering problem known as the clustered orienteering problem. In this problem, customers are grouped into clusters and a profit is associated with each cluster, collected only when all customers in the cluster are served. The proposed evolutionary algorithm, incorporating a backbone-based crossover operator and a destroy-and-repair mutation operator, outperforms existing algorithms on benchmark instances and sets new records on some instances. It also demonstrates scalability on large instances and has shown superiority over three state-of-the-art COP algorithms. The algorithm is also successfully applied to a dynamic version of the COP considering stochastic travel time.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Bjorn Bokelmann, Stefan Lessmann
Summary: Estimating treatment effects is an important task for data analysts, and uplift models provide support for efficient allocation of treatments. However, evaluating uplift models is challenging due to variance issues. This paper theoretically analyzes the variance of uplift evaluation metrics, proposes variance reduction methods based on statistical adjustment, and demonstrates their benefits on simulated and real-world data.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Congzheng Liu, Wenqi Zhu
Summary: This paper proposes a feature-based non-parametric approach to minimizing the conditional value-at-risk in the newsvendor problem. The method is able to handle both linear and nonlinear profits without prior knowledge of the demand distribution. Results from numerical and real-life experiments demonstrate the robustness and effectiveness of the approach.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Laszlo Csato
Summary: This paper compares the performance of the eigenvalue method and the row geometric mean as two weighting procedures. Through numerical experiments, it is found that the priorities derived from the two eigenvectors in the eigenvalue method do not always agree, while the row geometric mean serves as a compromise between them.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
Article
Management
Guowei Dou, Tsan-Ming Choi
Summary: This study investigates the impact of channel relationships between manufacturers on government policies and explores the effectiveness of positive incentives versus taxes in increasing social welfare. The findings suggest that competition may be more effective in improving sustainability and social welfare. Additionally, government incentives for green technology may not necessarily enhance sustainability.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2024)
