Article
Operations Research & Management Science
Hongbo Li, Hanyu Zhu, Linwen Zheng, Fang Xie
Summary: The main resources in software projects are human resources equipped with various skills, which makes software development a typical intelligence-intensive process. Therefore, effective human resource scheduling is indispensable for the success of software projects. We investigate the software project scheduling problem with uncertain activity durations (SPSP-UAD) and aim at obtaining effective scheduling policies for the problem.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
Humyun Fuad Rahman, Ripon K. Chakrabortty, Michael J. Ryan
Summary: This study introduces a mathematical model based on chance constraints to address the resource constrained project scheduling problem under dynamic environments. An efficient genetic algorithm based memetic algorithm is proposed to solve the model, showcasing excellent performance for solving instances with predefined but time-varying resource requests and availabilities.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
Gabriella Dellino, Carlo Meloni, Marco Pranzo, Marcella Sama
Summary: This article discusses the evaluation of expected shortfall or conditional value-at-risk for makespan in scheduling problems using temporal activity networks with type-1 fuzzy representation of integer-valued durations known to the scheduler. They propose and analyze a computational method to obtain fuzzy evaluation of the expected shortfall of makespan in a given schedule.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2022)
Article
Engineering, Industrial
Ugur Satic, Peter Jacko, Christopher Kirkbride
Summary: This study investigates the dynamic and stochastic resource-constrained multi-project scheduling problem and compares different solution approaches. The performance of the optimal reactive baseline algorithm is closest to the optimal policies, but its results are suboptimal. Alternative scheduling algorithms perform well with low project arrival probability but deteriorate quickly as the probability increases.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2022)
Article
Management
Mingxuan Zhao, Jian Zhou, Ke Wang, Athanasios A. Pantelous
Summary: In this paper, a novel operational law is proposed for calculating the credibility distributions of monotone functions of independent regular fuzzy numbers. This method is applied to study the project scheduling problem with partially (or fully) fuzzy activity durations. Three corresponding types of fuzzy models are formulated and shown to be convertible into crisp ones, which can be efficiently solved. Numerical experiments on public instances from the PSPLIB demonstrate the accuracy and efficiency of this approach.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
Yisong Yuan, Sudong Ye, Lin Lin, Mitsuo Gen
Summary: The paper focuses on studying an effective robust project scheduling method for prefabricated building (PB) construction projects. The proposed hybrid cooperative co-evolution algorithm (HCOEA) aims to reduce the impact of uncertain execution time on the overall project. Results show that the HCOEA outperforms existing state-of-the-art methods in terms of project scheduling efficiency and reliability.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Engineering, Industrial
Michal Kaut, Hajnalka Vaagen, Stein W. Wallace
Summary: The study reveals that when modeling design uncertainty with multiple alternatives and delaying decisions on the final alternative, the impact of stochastic and correlated activity durations is limited. In situations where alternative and substitutable solutions are available for a given design, correlations drive certain learning behaviors.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2021)
Article
Computer Science, Artificial Intelligence
Zhiguo Wang, Tsan Sheng Ng, Chee Khiang Pang
Summary: The study proposes a model for solving a project scheduling problem, introducing the concept of activity duration tolerance levels and a due-date achievement model based on activities exposure level. The model is shown to perform well compared to standard approaches across various performance measures.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Information Systems
Wuliang Peng, Dongmin Yu, Jiali Lin
Summary: This paper proposes a resource-constrained multi-project reactive scheduling problem with new project arrival to minimize the adjustment cost and achieve the deterministic multi-project scheduling goal. The scheduling problem has two stages, involving obtaining the shortest make-span and minimizing the adjustment cost. The computational experiments demonstrate the distinct advantages of the proposed method over existing methods.
Article
Management
Xueqi Wu, Shenghai Zhou
Summary: This paper addresses the problem of sequencing and scheduling appointments on multiple servers with stochastic service durations and customer arrivals. By formulating it as a two-stage integer program and deriving a deterministic mixed-integer linear program, the paper provides solutions to minimize the operational cost and improve system performance. The proposed integer L-shaped heuristic, enhanced by variable neighborhood descent, outperforms the deterministic program and integer L-shaped method, especially for large-scale problems, demonstrating significant impacts of appointment sequencing decisions on reducing operational cost.
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2022)
Article
Computer Science, Information Systems
Yining Yu, Zhe Xu, Song Zhao
Summary: This paper studies a stochastic distributed resource-constrained multi-project scheduling problem with multi-skilled staff. A two-stage algorithm with 12 priority rules is proposed, and the performance of these rules is evaluated on different instances. The experiment results show that two priority rules perform better than others, and our method outperforms other approaches, especially in large-size instances. Furthermore, our method is more conducive to shortening the CPU runtime on distributed problems than centralized methods.
Article
Energy & Fuels
Bowen Huang, Sen Huang, Xu Ma, Srinivas Katipamula, Di Wu, Robert Lutes
Summary: This paper presents the first attempt to address the uncertainty in zone temperature prediction with stochastic optimization. We proposed a novel formulation of stochastic optimization to handle process uncertainty in building control. Through simulation, we evaluated the proposed method and found that it works better when the uncertainty level is more significant.
Article
Computer Science, Artificial Intelligence
HaoJie Chen, Jian Zhang, Rong Li, Guofu Ding, Shengfeng Qin
Summary: This study proposes a novel hyper-heuristic based two-stage genetic programming framework (HHTGP) to solve the Stochastic Resource Constrained Multi-Project Scheduling Problem under New Project Insertions (SRCMPSP-NPI). It divides the evolution of genetic programming into generation and selection stages and establishes a multi-state combination scheduling mode with multiple priority rules (PRs) to realize resource-constrained project scheduling under stochastic activity duration and new project insertion for the first time.
APPLIED SOFT COMPUTING
(2022)
Article
Computer Science, Interdisciplinary Applications
Moritz Buchem, Tjark Vredeveld
Summary: The study investigates the application of fixed assignment policies in stochastic online scheduling problems to minimize total weighted expected completion time on uniform parallel machines. By introducing specific lower bounds for the uniform machine environment, performance guarantees are improved. In the Online-List model, it is shown that a greedy assignment policy is asymptotically optimal. Finally, a computational study is conducted to evaluate the performance of these policies in practice.
COMPUTERS & OPERATIONS RESEARCH
(2021)
Article
Computer Science, Artificial Intelligence
Abdullah Hulusi Kokcam, Orhan Engin
Summary: Determining resource requirements and activity durations accurately is crucial in project scheduling. This study proposes a hybrid algorithm to generate realistic project schedules with minimal risk of delay. The algorithm is tested on benchmark problems and a real-world case, showing promising results.
JOURNAL OF MULTIPLE-VALUED LOGIC AND SOFT COMPUTING
(2022)
Article
Management
Alessandro Agnetis, Ben Hermans, Roel Leus, Salim Rostami
Summary: This paper discusses a problem of determining the state of a system through costly tests before a deadline, as well as a related search problem with multiple searchers aiming to find a target before a deadline. Both problems are shown to be NP-hard and various algorithms are proposed to tackle them effectively. Extensive computational experiments suggest that different formulations perform better in different scenarios, and a local search procedure is shown to be effective in finding near-optimal solutions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Remote Sensing
Jungang Yan, Guopeng Song, Roel Leus, Zhenwei Hou, Zhongshan Zhang
Summary: Inter-satellite links (ISLs) optimization is crucial for developing global navigation satellite systems. A mathematical optimization model is proposed, and a rolling weight-matching method and a weight enhancement strategy are used to solve the ISL assignment problem. Simulation experiments demonstrate the effectiveness of the proposed methods.
Article
Management
Fan Yang, Morteza Davari, Wenchao Wei, Ben Hermans, Roel Leus
Summary: This article studies the scheduling problem of jobs with non-identical sizes and incompatible families on a single parallel-batching machine. By developing new linear programming formulations and heuristic algorithms, the objective of minimizing the total weighted completion time can be achieved.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Management
Yujie Zhao, Hong Zhou, Roel Leus
Summary: This paper investigates recovery strategies for supply chain enterprises under uncertain demand. It proposes financing strategies and recovery strategies for retailers to mitigate the negative impact of disruptions. The analysis considers the potential impact on regret, bankruptcy risk, and profit for different financing and recovery strategies.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Engineering, Manufacturing
Marie-Sklaerder Vie, Nicolas Zufferey, Roel Leus
Summary: Aircraft Landing Planning is a challenging task that requires considering the limited capacity of airport runways. This study proposes a mathematical formulation and simulation framework to address the problem while accounting for uncertainties. The research suggests that the use of different solution methods can lead to more effective and stable solutions, reducing delays and fuel costs while maintaining landing sequence stability.
JOURNAL OF SCHEDULING
(2022)
Article
Computer Science, Interdisciplinary Applications
N. Morandi, R. Leus, H. Yaman
Summary: We introduce a class of budgeted prize-collecting covering subgraph problems and develop a branch-and-cut framework and a Benders decomposition for their exact solution. We observe that the former algorithm generally has shorter computational times, but the latter can outperform the former in specific instances. Additionally, we validate our algorithmic frameworks for the cases where the subgraph is a cycle and a tree, and identify novel symmetry-breaking inequalities.
COMPUTERS & OPERATIONS RESEARCH
(2022)
Article
Management
Tom Demeulemeester, Dries Goossens, Ben Hermans, Roel Leus
Summary: This research investigates the one-sided matching problem where agents have preferences over objects but objects do not have preferences over agents. By decomposing probabilistic assignments, the researchers find the theoretically best worst-case number of assigned agents and propose two alternative column generation frameworks to achieve this decomposition.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Management
Ben Hermans, Roel Leus, Bart Van Looy
Summary: We develop project planning models that integrate scheduling and appropriation decisions for new product development projects. By considering the timing of development tasks and whether to use secrecy and patenting, we find that innovators can benefit from both methods during different project phases, contrary to the traditional view. Additionally, we discover that choosing secrecy may prolong the project's lead time, and it may be optimal to initiate tasks that expose the project earlier.
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2023)
Article
Operations Research & Management Science
Nicola Morandi, Roel Leus, Jannik Matuschke, Hande Yaman
Summary: In the TSP-mD problem, a truck and multiple drones work together to provide customer service in the minimum amount of time. The optimal solutions for TSP-mD may involve revisiting nodes and retraversing arcs. The necessity of arc retraversals has not been previously investigated, but excluding them may increase the optimal value under certain conditions. Furthermore, there is no polynomial-time heuristic that can approximate the metric TSP-mD within a constant factor unless P ≠ NP.
TRANSPORTATION SCIENCE
(2023)
Proceedings Paper
Automation & Control Systems
Maria-Luisa Munoz-Diaz, Alejandro Escudero-Santana, Roel Leus, Antonio Lorenzo-Espejo
Summary: This paper introduces two mixed linear programming models (MILP) for single-station production scheduling, which utilize continuous and discrete forms of time representation. Both models address the sequencing and assignment of tasks for non-identical parallel machines. The models are solved using Gurobi Optimizer and the results are presented in a table, displaying the objective function's value and runtimes.
IOT AND DATA SCIENCE IN ENGINEERING MANAGEMENT
(2023)
Article
Operations Research & Management Science
Nicola Morandi, Roel Leus, Hande Yaman
Summary: We extend the classical orienteering problem to incorporate multiple drones that cooperate with a truck. We provide a linear programming formulation and a tailored algorithm to solve the problem, demonstrating its effectiveness through computational experiments.
TRANSPORTATION SCIENCE
(2023)
Article
Computer Science, Interdisciplinary Applications
Boshuai Zhao, Roel Leus
Summary: This paper proposes a method to optimize the truck platooning system's routes and schedules, improves an existing heuristic, and demonstrates better performance under certain conditions.
COMPUTERS & OPERATIONS RESEARCH
(2024)
Article
Computer Science, Interdisciplinary Applications
Guopeng Song, Roel Leus
Summary: This study investigates parallel machine scheduling with uncertain job processing times and adopts three different modeling paradigms to handle uncertainty. Generic solution methods are proposed and compared, and general lessons are learned regarding the choice between different frameworks for planning under uncertainty.
INFORMS JOURNAL ON COMPUTING
(2022)
Proceedings Paper
Computer Science, Artificial Intelligence
Nicolas Zufferey, Marie-Sklaerder Vie, Roel Leus
Summary: This study focuses on the Aircraft Landing Planning (ALP) problem, aiming to minimize delays and satisfy separation constraints. By determining the landing sequence, associated landing times, and Holding-Stack Patterns (HSPs), delays can be reduced by approximately 50% on average.
OPTIMIZATION IN ARTIFICIAL INTELLIGENCE AND DATA SCIENCES
(2022)
Article
Computer Science, Interdisciplinary Applications
Ben Hermans, Roel Leus, Jannik Matuschke
Summary: This paper presents new algorithms for the expanding search problem, which involves searching a graph for a target hidden in one of the nodes according to a known probability distribution. The proposed algorithms, including a branch-and-cut procedure, a greedy algorithm, and a local search procedure, have been analyzed both experimentally and theoretically, showing improvement on existing methods and providing the first constant-factor approximation guarantee for this problem.
INFORMS JOURNAL ON COMPUTING
(2022)
