Article
Management
Tessa Borgonjon, Broos Maenhout
Summary: The paper investigates the problem of personnel task rescheduling with task retiming, proposing a branch-and-price procedure for recovering the personnel task schedule and showing its performance through computational experiments with different optimization principles.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Engineering, Electrical & Electronic
Yuyang Du, Soung Chang Liew, Yulin Shao
Summary: This research proposes a new IFDMA transceiver design that reduces complexity and improves computational efficiency. By exploiting the correspondence between IFDMA signal processing and the Cooley-Tukey IFFT/FFT algorithm, IFDMA streams can be inserted/extracted at different stages of an IFFT/FFT module. The use of the multi-priority scheduling algorithm further reduces computation time, and experimental results show promising performance on specific hardware implementation.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Zhenwei Zhu, Xionghui Zhou
Summary: This paper studies an uncertain flexible job shop scheduling problem and proposes a novel multi-objective multiple-micro-swarm leadership hierarchy-based optimization algorithm to solve it, demonstrating its effectiveness through extensive experiments.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Automation & Control Systems
Qing-Hua Zhu, Huan Tang, Jia-Jie Huang, Yan Hou
Summary: This work proposes a novel scheduling method called matching and multi-round allocation (MMA) to optimize task completion time and total cost in a multi-cloud environment, ensuring security and reliability constraints are met.
IEEE-CAA JOURNAL OF AUTOMATICA SINICA
(2021)
Article
Engineering, Manufacturing
Felix Happach
Summary: The paper considers a variant of the NP-hard problem of assigning jobs to machines to minimize the completion time of the last job. It introduces a different type of precedence relation called OR-precedence and proves that a simple List Scheduling algorithm has an approximation guarantee of 2. Additionally, a polynomial-time algorithm is presented that can solve the problem to optimality when preemptions are allowed.
JOURNAL OF SCHEDULING
(2021)
Article
Management
Zhujun Liu, Ilkyeong Moon, Ruiyou Zhang
Summary: This research addresses the flexible vehicle scheduling problem with precedence constraints in scenic areas. A three-indexed integer linear programming model is introduced along with an index-reduction strategy. A math-heuristic route-segment generation algorithm is designed to solve the problem efficiently, particularly for large-sized instances. Experiments validate the effectiveness of the proposed algorithm, which provides better solutions in less time, and shed light on the trade-off between tourists' satisfaction and the cost.
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH
(2023)
Article
Computer Science, Information Systems
Sowndarya Sundar, Jaya Prakash Champati, Ben Liang
Summary: This paper studies the task scheduling and offloading problem in a cloud computing system with multiple users, proposing an efficient framework and algorithm for finding solutions that minimize the weighted sum completion time while satisfying budget constraints.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2022)
Article
Economics
Weitiao Wu, Yue Lin, Ronghui Liu, Wenzhou Jin
Summary: Electric buses have significant environmental and social benefits, but their large-scale adoption faces technical challenges and power grid safety issues. This paper proposes a bi-objective multi-depot electric vehicle scheduling problem that considers time-of-use pricing and peak load risk, and presents a tailored branch-and-price method to solve it.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2022)
Article
Thermodynamics
Ji Wu, Hao Su, Jinhao Meng, Mingqiang Lin
Summary: The impacts of large-scale electric vehicles charging on the power grid and the lack of charging infrastructure can hinder the promotion of EVs. To address this issue, a charging scheduling strategy based on time-of-use price is proposed, considering the least cost of charging as the objective function and the constraints of charging pile number and instantaneous power. Through the simulation of EV charging behavior using the Monte Carlo method and solving the optimization problem using the adaptive genetic algorithm, each EV is assigned a specific charging pile that meets its charging demand. Experimental results show that this method achieves better results than comparative methods while ensuring the safe operation of charging stations and reducing peak and valley load on the grid.
Article
Computer Science, Artificial Intelligence
Huilong Fan, Zhan Yang, Xi Zhang, Shimin Wu, Jun Long, Limin Liu
Summary: This paper investigates the task scheduling timeliness problem on satellite networks and proposes a multi-layer network graph aggregation model to address the complex relationships between tasks in a multi-satellite and multi-task scenario. The experimental results demonstrate the distinct advantages and advancements of the proposed method.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Transportation Science & Technology
Faisal Alkaabneh, Ali Diabat
Summary: The application of optimization techniques to home care service planning has gained attention due to the increasing demand for dedicated care. A mixed integer programming model is developed to simultaneously consider nurse-patient assignment, nurse workday scheduling, and nurse routing. The multi-objective model aims to minimize costs and maximize compatibility between nurses and patients. Computational studies demonstrate the superiority of the developed approaches in terms of cost savings, improved compatibility, and solving efficiency.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2023)
Article
Computer Science, Theory & Methods
Vaneet Aggarwal, Tian Lan, Dheeraj Peddireddy
Summary: This paper introduces the concept of fractional precedence constraints in programming models, and proposes a new class of preemptive scheduling algorithms for jobs on unrelated machines with arbitrary processing speeds. By establishing sufficient and necessary conditions for feasible job schedules, and utilizing a novel matrix decomposition method, the paper presents an efficient scheduling algorithm that is a Polynomial-Time Approximation Scheme (PTAS) with an approximation bound of 1 + epsilon.
JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING
(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
Computer Science, Interdisciplinary Applications
Onur Ozturk
Summary: This paper investigates a scheduling problem involving simultaneous serial and parallel batching decisions, aiming to minimize total flow time and total weighted tardiness. The problem is formulated as an integer linear programming model and solved using a column generation algorithm integrated in a branch and bound tree. A highly efficient heuristic branching technique is used for the total weighted tardiness objective, with optimality proven for the total flow time objective. Numerical test results demonstrate the algorithm's ability to handle large instances within reasonable computational times.
COMPUTERS & OPERATIONS RESEARCH
(2022)
Article
Computer Science, Information Systems
Jiong Lou, Zhiqing Tang, Songli Zhang, Weijia Jia, Wei Zhao, Jie Li
Summary: In Mobile Edge Computing (MEC), latency-sensitive mobile applications with dependent tasks can be scheduled to edge or cloud servers to reduce latency and execution costs. However, existing algorithms based on deadline distribution lack a global view of the future impacts on descendant tasks in heterogeneous MEC. To address this, we propose a low-complexity scheduling algorithm that considers a single task's future impacts in two stages, resulting in substantial advantages over baselines in both online and offline scenarios.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2023)
Article
Automation & Control Systems
Cesar A. Saenz-Alanis, V. D. Jobish, M. Angelica Salazar-Aguilar, Vincent Boyer
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2016)
Article
Management
Roberto Cantu-Funes, M. Angelica Salazar-Aguilar, Vincent Boyer
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
(2018)
Article
Engineering, Industrial
Jobish Vallikavungal Devassia, M. Angelica Salazar-Aguilar, Vincent Boyer
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2018)
Article
Computer Science, Interdisciplinary Applications
V. Boyer, D. El Baz, M. Elkihel
COMPUTERS & INDUSTRIAL ENGINEERING
(2011)
Article
Computer Science, Interdisciplinary Applications
V. Boyer, D. El Baz, M. Elkihel
COMPUTERS & OPERATIONS RESEARCH
(2012)
Article
Engineering, Industrial
Vincent Boyer, Didier El Baz, Moussa Elkihel
EUROPEAN JOURNAL OF INDUSTRIAL ENGINEERING
(2010)
Article
Management
V. Boyer, M. Elkihel, D. El Baz
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2009)
Article
Automation & Control Systems
Didier El Baz, Vincent Boyer, Julien Bourgeois, Eugen Dedu, Kahina Boutoustous
Article
Economics
Alejandro Andrade-Michel, Yasmin A. Rios-Solis, Vincent Boyer
Summary: This study proposes an integrated approach for the bus vehicle and driver scheduling problem, aiming to reduce the number of no-covered trips by considering driver's reliability information and improve user satisfaction. By comparing constraint programming model with variable neighborhood search, it demonstrates significant gains in covered trips when drivers' reliability is taken into account.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2021)
Article
Computer Science, Hardware & Architecture
Didier El Baz, Bilal Fakih, Romeo Sanchez Nigenda, Vincent Boyer
Summary: This paper introduces parallel planning algorithms derived from best-first search for shared memory architectures to improve computational performance. The algorithms, based on the asynchronous work pool paradigm, maintain good thread occupancy in multi-core CPUs. By selecting nodes for expansion from an ordered global list of states stored in shared memory, the algorithms efficiently solve most domains without incurring higher solutions costs.
JOURNAL OF SUPERCOMPUTING
(2022)
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)
Proceedings Paper
Computer Science, Theory & Methods
V. Boyer, D. El Baz, M. Elkihel
CIE: 2009 INTERNATIONAL CONFERENCE ON COMPUTERS AND INDUSTRIAL ENGINEERING, VOLS 1-3
(2009)
