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Journal articles on the topic 'The schedule optimization'

Author: Grafiati

Published: 7 June 2025

Last updated: 2 August 2025

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1

Berg, Bjorn P., S. Ayca Erdogan, Jennifer Mason Lobo, and Kathryn Pendleton. "A Method for Balancing Provider Schedules in Outpatient Specialty Clinics." MDM Policy & Practice 5, no. 2 (2020): 238146832096306. http://dx.doi.org/10.1177/2381468320963063.

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Background. Variability in outpatient specialty clinic schedules contributes to numerous adverse effects including chaotic clinic settings, provider burnout, increased patient waiting times, and inefficient use of resources. This research measures the benefit of balancing provider schedules in an outpatient specialty clinic. Design. We developed a constrained optimization model to minimize the variability in provider schedules in an outpatient specialty clinic. Schedule variability was defined as the variance in the number of providers scheduled for clinic during each hour the clinic is open.

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Albogamy, Fahad R. "Optimal Energy Consumption Scheduler Considering Real-Time Pricing Scheme for Energy Optimization in Smart Microgrid." Energies 15, no. 21 (2022): 8015. http://dx.doi.org/10.3390/en15218015.

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Energy consumption schedulers have been widely adopted for energy management in smart microgrids. Energy management aims to alleviate energy expenses and peak-to-average ratio (PAR) without compromising user comfort. This work proposes an energy consumption scheduler using heuristic optimization algorithms: Binary Particle Swarm Optimization (BPSO), Wind Driven Optimization (WDO), Genetic Algorithm (GA), Differential Evolution (DE), and Enhanced DE (EDE). The energy consumption scheduler based on these algorithms under a price-based demand response program creates a schedule of home appliances

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Schrage, Rico, Paul Hendrik Tiemann, and Astrid Niesse. "A Multi-Criteria Metaheuristic Algorithm for Distributed Optimization of Electric Energy Storage." ACM SIGEnergy Energy Informatics Review 2, no. 4 (2022): 44–59. http://dx.doi.org/10.1145/3584024.3584029.

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The distributed schedule optimization of energy storage constitutes a challenge. Such algorithms often expect an input set containing all feasible schedules and, therefore, require searching the schedule space efficiently. However, it is hardly possible to accomplish this with energy storage due to its high flexibility. In this paper, the problem is introduced in detail and addressed by a metaheuristic algorithm, which generates a preselection of schedules. Two contributions are presented to achieve this goal: First, an extension for a distributed schedule optimization allowing a simultaneous

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Saber, A. Y., Wahed Newaz, and A. K. M. Zaidi Sattar. "Generator Scheduling (a Combinatorial Optimization Problem) by Annealing Method." DIU Journal of Science & Technology 2, no. 1 (2024): 72–80. https://doi.org/10.5281/zenodo.13674845.

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Generator scheduling is acombinatorial optimization problem and thispaper presents a new version of annealing (SA)method to model and solve the schedulingproblem. Firstly, solution is decomposed intohourly schedules and each hourly schedule ismodified by decomposed-SA using bits flipping. Ifthe generated new hourly schedule is better, byconvention it is accepted deterministically. Aworse hourly schedule is accepted withtemperature dependent SA probability. A newsolution consists of these hourly schedules ofentire scheduling period after repair as unit-wiseconstraints may not be fulfilled at th

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Guo, Fengdi, Jeremy Gregory, and Randolph Kirchain. "Probabilistic Life-Cycle Cost Analysis of Pavements Based on Simulation Optimization." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 5 (2019): 389–96. http://dx.doi.org/10.1177/0361198119838984.

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Life-cycle cost analysis (LCCA) is a way to evaluate the long-term cost effectiveness of different pavement designs or treatment actions. Owing to the existence of uncertainties, many probabilistic LCCA models have been proposed. They mainly use a prescribed treatment schedule or determine schedules by mechanistic-empirical analysis, potentially leading to the overestimation of life-cycle cost (LCC). In this paper, a new probabilistic simulation-optimization LCCA model is proposed. This new model determines treatment schedules by minimizing total LCC, including agency and user cost, which is d

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Hao, Wang, Xiaobo Zhang, Baokuo Li, Zhanxue Wang, and Dawei Li. "A Combined Optimization Method for the Transition Control Schedules of Aero-Engines." Aerospace 12, no. 2 (2025): 144. https://doi.org/10.3390/aerospace12020144.

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A well designed transition control schedule can enable the engine to quickly and smoothly transition from one operating state to another, thereby enhancing the maneuverability of the aircraft. Although traditional pointwise optimization methods are fast in solving the transition control schedules, their optimized control schedules suffer from fluctuation problems. While global optimization methods can suppress fluctuation problems, their slow solving speed makes them unsuitable for engineering applications. In this paper, a combined optimization method for the transition control schedules of a

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Zhao, Mengqi, Xiaoling Wang, Jia Yu, Lei Bi, Yao Xiao, and Jun Zhang. "Optimization of Construction Duration and Schedule Robustness Based on Hybrid Grey Wolf Optimizer with Sine Cosine Algorithm." Energies 13, no. 1 (2020): 215. http://dx.doi.org/10.3390/en13010215.

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Construction duration and schedule robustness are of great importance to ensure efficient construction. However, the current literature has neglected the importance of schedule robustness. Relatively little attention has been paid to schedule robustness via deviation of an activity’s starting time, which does not consider schedule robustness via structural deviation caused by the logical relationships among activities. This leads to a possibility of deviation between the planned schedule and the actual situation. Thus, an optimization model of construction duration and schedule robustness is p

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Tao, Mei, Lan Ma, and Yiming Ma. "Flight schedule adjustment for hub airports using multi-objective optimization." Journal of Intelligent Systems 30, no. 1 (2021): 931–46. http://dx.doi.org/10.1515/jisys-2020-0114.

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Abstract Based on the concept of “passengers self-help hubbing,” we build a flight schedule optimization model where maximizing the number of feasible flight connections, indicating transfer opportunities, as one objective and minimizing total slot displacements as the other objective. At the same time, the “Demand Smoothing Model” is introduced into the flight schedule optimization model to reduce the queuing delays for arrival and departure flights. We take into account all aircraft itineraries, the difficulty level of schedule coordination, and the maximum displacement of any single flight

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Yu, Jingyi, Minghua Hu, Zheng Zhao, and Bin Jiang. "Flight Schedule Optimization Considering Fine-Grained Configuration of Slot Coordination Parameters." Aerospace 11, no. 9 (2024): 763. http://dx.doi.org/10.3390/aerospace11090763.

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In response to the rapid growth of air passenger and cargo transportation services and the sharp increase in congestion at various airports, it is necessary to optimize the allocation of flight schedules. On the basis of reducing the total airport delay time and ensuring the total deviation of flight schedules applied by airlines, it is necessary to consider finely configuring flight schedules with slot coordination parameters, introducing a 5 min slot coordination parameter, and optimizing airport flight schedules in different time periods. This article considers factors such as flight schedu

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Su, Ruiye, Leishan Zhou, and Jinjin Tang. "Locomotive Schedule Optimization for Da-qin Heavy Haul Railway." Mathematical Problems in Engineering 2015 (2015): 1–14. http://dx.doi.org/10.1155/2015/607376.

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The main difference between locomotive schedule of heavy haul railways and that of regular rail transportation is the number of locomotives utilized for one train. One heavy-loaded train usually has more than one locomotive, but a regular train only has one. This paper develops an optimization model for the multilocomotive scheduling problem (MLSP) through analyzing the current locomotive schedule of Da-qin Railway. The objective function of our paper is to minimize the total number of utilized locomotives. The MLSP is nondeterministic polynomial (NP) hard. Therefore, we convert the multilocom

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Lee, Gi-Ho, Jae-Young Park, Seung-Jun Ham, and Young-Jin Kim. "Comparative Study on Optimization Solvers for Implementation of a Two-Stage Economic Dispatch Strategy in a Microgrid Energy Management System." Energies 13, no. 5 (2020): 1096. http://dx.doi.org/10.3390/en13051096.

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A microgrid energy management system (MEMS) optimally schedules the operation of dispatchable distributed energy resources to minimize the operation costs of microgrids (MGs) via an economic dispatch (ED). Actual ED implementation in the MEMS relies on an optimization software package called an optimization solver. This paper presents a comparative study of optimization solvers to investigate their suitability for ED implementation in the MEMS. Four optimization solvers, including commercial as well as open-source-based ones, were compared in terms of their computational capability and optimiz

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Drake, Megan, Haoming Li, Enzo Sacchetti, Inigo Saez, and Christopher Shutler. "United Health Services: Transportation Optimization." Industrial and Systems Engineering Review 7, no. 1 (2019): 38–43. http://dx.doi.org/10.37266/iser.2019v7i1.pp38-43.

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This project is based off the desire to improve the efficiency and customer service of the United Health Services transportation departments to minimize fuel costs, turnaround time, mileage, and duplicate deliveries by May 2019. United Health Services, a medical care provider in southern New York State, has two delivery and transportation departments that service 60 facilities. Materials Handling has two drivers and a weekly schedule and oversees the delivery of various medical supplies such as bandages, syringes, and crutches. External Transportation is staffed by 12 drivers and delivers time

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AZEMSHA, Siarhei, Irina KRAVCHENYA, Yuriy VOVK, Oleg LYASHUK, and Iryna VOVK. "SCHEDULING TECHNIQUE OF ROUTE VEHICLES ON DUPLICATING STRETCHES." Scientific Journal of Silesian University of Technology. Series Transport 113 (December 1, 2021): 5–16. http://dx.doi.org/10.20858/sjsutst.2021.113.1.

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Schedule optimization is a proven strategy to improve service quality for public transport networks. However, current research mostly optimizes schedule design using prior knowledge of users’ routings, ignoring the optimization of public transport schedules on duplicating stretches of route vehicles. This article presents a new alignment technique of time intervals between consecutive vehicles of different routes on duplicating stretches, considering existing public transport networks in attaining optimization of public transport schedule. Scheduling technique of route vehicles on duplicating

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Zhou, Wenliang, Junli Tian, Jin Qin, Lianbo Deng, and TangJian Wei. "Optimization of Multiperiod Mixed Train Schedule on High-Speed Railway." Discrete Dynamics in Nature and Society 2015 (2015): 1–14. http://dx.doi.org/10.1155/2015/107048.

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For providing passengers with periodic operation trains and making trains’ time distribution better fit that of passengers, the multiperiod mixed train schedule is first proposed in this paper. It makes each type of train having same origin, destination, route, and stop stations operate based on a periodic basis and allows different types of train to have various operation periods. Then a model of optimizing multiperiod mixed train schedule is built to minimize passengers generalized travel costs with the constraints of trains of same type operating periodically, safe interval requirements of

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Panchal, Pratik Bhikhubhai. "Schedule Optimization for Dry Dock Construction Projects in Spatially Constrained Naval Facilities." IOSR Journal of Mechanical and Civil Engineering 22, no. 1 (2025): 75–85. https://doi.org/10.9790/1684-2201017585.

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Construction of dry docks in spatially restricted naval plants is deemed unique project endeavours that are characterized by the need to consider scheduled timing to prevent loss of time, hindered work dislocation, and safety concerns in the limited workspace and relying on extensive interdependency in the activities. In this study, the focus is on developing optimization approaches to dry dock construction schedules where phased segmentation of the space solutions is interrelated, floating and semi-submersible platforms are used temporarily to increase working space and crane logistics are pl

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Tietjen, Jan, Christof Büskens, and Matthias Knauer. "Time Schedule Optimization of Satellites." PAMM 8, no. 1 (2008): 10805–6. http://dx.doi.org/10.1002/pamm.200810805.

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Dietz, Dennis C. "Computing the Expected Cost of an Appointment Schedule for Statistically Identical Customers with Probabilistic Service Times." Scientific World Journal 2014 (2014): 1–5. http://dx.doi.org/10.1155/2014/949726.

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A cogent method is presented for computing the expected cost of an appointment schedule where customers are statistically identical, the service time distribution has known mean and variance, and customer no-shows occur with time-dependent probability. The approach is computationally efficient and can be easily implemented to evaluate candidate schedules within a schedule optimization algorithm.

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Bielokha, H., and V. Sychova. "OPTIMIZATION OF ELECTRICAL LOAD SCHEDULES BY AN AGGREGATOR IN LOCAL ELECTRICAL POWER SYSTEMS." Praci Institutu elektrodinamiki Nacionalanoi akademii nauk Ukraini 2023, no. 66 (2023): 84–89. http://dx.doi.org/10.15407/publishing2023.66.084.

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The market operation of the electricity distribution system has gained significant expansion due to the growing use of renewable and distributed sources. This paper presents strategies for optimizing load schedules by aggregators of local systems. Optimization of load schedules is to minimize the total costs of the supplier to reduce the cost of electricity and lower prices for the consumer. In local systems, which include diesel generators, the main component that most affects the price per 1 kW is the consumption of primary fuel of diesel generators. The objective function proposed in this s

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Sakalauskas, Leonidas, and Gražvydas Felinskas. "OPTIMIZATION OF RESOURCE‐CONSTRAINED PROJECT SCHEDULES BY SIMULATED ANNEALING AND VARIABLE NEIGHBORHOOD SEARCH." Technological and Economic Development of Economy 12, no. 4 (2006): 307–13. http://dx.doi.org/10.3846/13928619.2006.9637759.

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Applications of information technologies are often related to making some schedules, timetables of tasks or jobs with constrained resources. In this paper we consider job scheduling and optimization algorithms related to resources, time and other constraints. Schedule optimization procedures, based on schedule coding by priority list of jobs, are created and investigated. Optimal priority list of jobs is found by approaching algorithms of local and global search, namely, random search and simulated annealing methods with the variable neighborhood, defined by the decoding procedure applied. Com

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Martiano, M., Yoshida Sari, and Farid Akbar. "Analysis and Optimization of the K-Means Algorithm in Determining Course Scheduling." Journal of Information System Research (JOSH) 5, no. 1 (2023): 134–41. http://dx.doi.org/10.47065/josh.v5i1.4343.

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Preparation of course schedules is the core activity of learning and learning. This is felt by study programs, where assignments are arranged through lecturer assignments, to class determination and class schedule dissolution, therefore the right application is needed to be able to arrange schedules automatically, then by using the k-means method you can arrange schedules correctly , in designing this application requires a prototyping application development method which gives good results where the clusters formed reach 17 clusters where the course schedule is made with the results of the Me

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Liu, Xiaodong, Juan Du, Xingqun Cheng, Yan Zhu, and Jian Ma. "An Adaptive Shift Schedule Design Method for Multi-Gear AMT Electric Vehicles Based on Dynamic Programming and Fuzzy Logical Control." Machines 11, no. 9 (2023): 915. http://dx.doi.org/10.3390/machines11090915.

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This paper proposes an adaptive shift schedule design framework based on dynamic programming (DP) algorithm and fuzzy logical control to promote the shift schedule’s adaptability whilst improving the comprehensive performance of the multi-gear automated manual transmission (AMT) electric vehicles in real-time application. First, the DP algorithm is employed to extract an offline optimal gear-shift schedule based on a set of driving conditions, including 11 groups of typical driving cycles. Second, a fuzzy logical controller is formulated considering the variation in the vehicle load and accele

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Xie, J., S. C. Wong, S. Zhan, S. M. Lo, and Anthony Chen. "Train schedule optimization based on schedule-based stochastic passenger assignment." Transportation Research Part E: Logistics and Transportation Review 136 (April 2020): 101882. http://dx.doi.org/10.1016/j.tre.2020.101882.

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Morozs, Nils, Paul D. Mitchell, and Yuriy Zakharov. "LTDA-MAC v2.0: Topology-Aware Unsynchronized Scheduling in Linear Multi-Hop UWA Networks." Network 1, no. 1 (2021): 2–10. http://dx.doi.org/10.3390/network1010002.

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This paper investigates the use of underwater acoustic sensor networks (UASNs) for subsea asset monitoring. In particular, we focus on the use cases involving the deployment of networks with line topologies, e.g., for monitoring oil and gas pipelines. The Linear Transmit Delay Allocation MAC (LTDA-MAC) protocol facilitates efficient packet scheduling in linear UASNs without clock synchronization at the sensor nodes. It is based on the real-time optimization of a packet schedule for a given network deployment. In this paper, we present a novel greedy algorithm for real-time optimization of LTDA

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Tabibian, Behzad, Utkarsh Upadhyay, Abir De, Ali Zarezade, Bernhard Schölkopf, and Manuel Gomez-Rodriguez. "Enhancing human learning via spaced repetition optimization." Proceedings of the National Academy of Sciences 116, no. 10 (2019): 3988–93. http://dx.doi.org/10.1073/pnas.1815156116.

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Spaced repetition is a technique for efficient memorization which uses repeated review of content following a schedule determined by a spaced repetition algorithm to improve long-term retention. However, current spaced repetition algorithms are simple rule-based heuristics with a few hard-coded parameters. Here, we introduce a flexible representation of spaced repetition using the framework of marked temporal point processes and then address the design of spaced repetition algorithms with provable guarantees as an optimal control problem for stochastic differential equations with jumps. For tw

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Gu, Xiao Wei, Peng Fei Wang, Qing Wang, You Yi Zheng, Jian Ping Liu, and Bin Chen. "Simultaneous Optimization of Final Pit and Production Schedule in Open-Pit Coal Mines." Advanced Materials Research 323 (August 2011): 222–28. http://dx.doi.org/10.4028/www.scientific.net/amr.323.222.

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A dynamic sequencing method has been developed that can simultaneously optimize the final pit and the production schedule of an open-pit coal mine. The method first establishes a geological seam model of a bedded coal deposit which estimates the relevant attributes of coal seams at the center of each block on the X-Y plane. Based on the seam model, a sequence of “geologically optimum final pits” is generated and, in each of these pits, a sequence of “geologically optimum push-backs” is generated. The geologically optimum push-backs are then put into a dynamic programming scheme and the best pr

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El-Sayegh, Sameh. "Resource levelling optimization model considering float loss impact." Engineering, Construction and Architectural Management 25, no. 5 (2018): 639–53. http://dx.doi.org/10.1108/ecam-10-2016-0229.

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Purpose The purpose of this paper is to propose a Non-Linear Integer Programming (NLIP) model that solves the resource leveling problem while reducing the negative effect of the total float loss on risk. Design/methodology/approach An NLIP model is formulated to solve the resource leveling optimization problem incorporating float loss cost (FLC). The proposed model is implemented using “What’s Best solver” for Excel. The FLC is calculated using the float commodity approach. An example is solved using the proposed model in order to illustrate its applicability. Sensitivity analysis is also perf

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Tong, Qianping, Xingji Jin, Timo Pukkala, Lihu Dong, and Fengri Li. "Stochastic Optimization of the Management Schedule of Korean Pine Plantations." Forests 15, no. 6 (2024): 935. http://dx.doi.org/10.3390/f15060935.

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Korean pine is one of the most important tree species in northeastern China, where Korean pine plantations produce timber and edible seeds. Often, seeds create more income than timber. Predicting the timber and cone yields of alternative management schedules of the plantations involves uncertainty because the future climatic conditions for tree growth and cone production are unknown. This study developed a simulation model that generates stochastic variation around the predictions of tree growth and cone yield models, allowing the forest manager to seek cutting schedules that maximize the expe

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Wei, Hai Min, and Rong Guang Liu. "The Optimization of Project Time-Cost Based on Particle Swarm Optimization Algorithm." Advanced Materials Research 791-793 (September 2013): 1423–26. http://dx.doi.org/10.4028/www.scientific.net/amr.791-793.1423.

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Project schedule management is the management to each stage of the degree of progress and project final deadline in the project implementation process. Its purpose is to ensure that the project can meet the time constraints under the premise of achieving its overall objectives.When the progress of schedule found deviation in the process of schedule management ,the progress of the plan which have be advanced previously need to adjust.This article mainly discussed to solve the following two questions:establish the schedule optimization model by using the method of linear;discuss the particle swa

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DING, GUOSHENG, and SHIJIE SUN. "SINGLE MACHINE FAMILY SCHEDULING WITH TWO COMPETING AGENTS TO MINIMIZE MAKESPAN." Asia-Pacific Journal of Operational Research 28, no. 06 (2011): 773–85. http://dx.doi.org/10.1142/s021759591100334x.

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We consider two-agent scheduling on a single machine, where there are job families and setup requirements exist between these families. Each agent's objective function is to minimize his own makespan. One of our goals is to find the optimal solution for one agent with a constraint on the other agent's makespan (constrained optimization). This problem is equivalent to the caudate Knapsack problem that we define in the paper. The other goal is to find single nondominated schedules (i.e., such that a better schedule for one of the two agents necessarily result in a worse schedule of the other age

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Kim, Taehoon, and Yong-Woo Kim. "Proactive Production Scheduling Approach for Off-Site Construction with Due Date Uncertainty." Applied Sciences 14, no. 23 (2024): 11017. http://dx.doi.org/10.3390/app142311017.

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This study proposes a robust precast concrete (PC) production scheduling model for PC construction projects with schedule uncertainty by adopting a proactive scheduling approach. The proposed model consists of a PC production simulation module that simulates and evaluates the total tardiness of the schedule at a certain confidence level with contractor schedule uncertainty and a GA-based production schedule optimization module that finds an optimal schedule through iterative schedule generation and evaluation using a PC production simulation module. The experimental study shows that the propos

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Fang, Xu. "Research of Construction Schedule Optimization using Particle Swarm Optimization." Advanced Materials Research 452-453 (January 2012): 441–45. http://dx.doi.org/10.4028/scientific5/amr.452-453.441.

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Fang, Xu. "Research of Construction Schedule Optimization using Particle Swarm Optimization." Advanced Materials Research 452-453 (January 2012): 441–45. http://dx.doi.org/10.4028/www.scientific.net/amr.452-453.441.

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The particle swarm optimization (PSO)-based approach to resolve the resource-constrained project scheduling problem with the objective of minimizing project duration is introduced in this paper. Computational analyses are provided so as to investigate the performance of the PSO-based approach for the resource-constrained project scheduling problem. The results shows that it is feasible to apply PSO to construction schedule optimization.

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Zeng, Lishan, Jun Zhang, and Mohan Sarovar. "Schedule path optimization for adiabatic quantum computing and optimization." Journal of Physics A: Mathematical and Theoretical 49, no. 16 (2016): 165305. http://dx.doi.org/10.1088/1751-8113/49/16/165305.

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Kristiadi, David, and Rudy Hartanto. "Genetic Algorithm for lecturing schedule optimization." IJCCS (Indonesian Journal of Computing and Cybernetics Systems) 13, no. 1 (2019): 83. http://dx.doi.org/10.22146/ijccs.43038.

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Scheduling is a classic problem in lecturing. Rooms, lecturers, times and scheduling constraints must be managed well to get an optimal schedule. University of Boyolali (UBY) also encounter the same scheduling problems. The problem was tried to be solved by building a library based on Genetic Algorithm (GA). GA is a computation method which inspired by natural selection. The computation consists of some operators i.e. Tournament Selection, Uniform Crossover, Weak Parent Replacement and two mutation operators (Interchanging Mutation and Violated Directed Mutation (VDM)). The two mutation method

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Hegazy, Tarek, and Ehab Kamarah. "Schedule optimization for scattered repetitive projects." Automation in Construction 133 (January 2022): 104042. http://dx.doi.org/10.1016/j.autcon.2021.104042.

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Koohi, Sina Zangbari, Nor Asilah Wati Abdul Hamid, Mohamed Othman, and Gafurjan Ibragimov. "ROA-CONS: Raccoon Optimization for Job Scheduling." Symmetry 13, no. 12 (2021): 2270. http://dx.doi.org/10.3390/sym13122270.

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High-performance computing comprises thousands of processing powers in order to deliver higher performance computation than a typical desktop computer or workstation in order to solve large problems in science, engineering, or business. The scheduling of these machines has an important impact on their performance. HPC’s job scheduling is intended to develop an operational strategy which utilises resources efficiently and avoids delays. An optimised schedule results in greater efficiency of the parallel machine. In addition, processes and network heterogeneity is another difficulty for the sche

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Chahyadi, Ferdi, Azhari SN, and Hendra Kurniawan. "Hospital Nurse Scheduling Optimization Using Simulated Annealing and Probabilistic Cooling Scheme." IJCCS (Indonesian Journal of Computing and Cybernetics Systems) 12, no. 1 (2018): 21. http://dx.doi.org/10.22146/ijccs.23056.

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Nurse’s scheduling in hospitals becomes a complex problem, and it takes time in its making process. There are a lot of limitation and rules that have to be considered in the making process of nurse’s schedule making, so it can fulfill the need of nurse’s preference that can increase the quality of the service. The existence variety of different factors that are causing the nurse scheduling problem is so vast and different in every case. The study is aimed to develop a system used as an equipment to arrange nurse’s schedule. The working schedule obtained will be checked based on the constraints

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Salama, Tarek, and Osama Moselhi. "Multi-objective optimization for repetitive scheduling under uncertainty." Engineering, Construction and Architectural Management 26, no. 7 (2019): 1294–320. http://dx.doi.org/10.1108/ecam-05-2018-0217.

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Purpose The purpose of this paper is to present a newly developed multi-objective optimization method for the time, cost and work interruptions for repetitive scheduling while considering uncertainties associated with different input parameters. Design/methodology/approach The design of the developed method is based on integrating six modules: uncertainty and defuzzification module using fuzzy set theory, schedule calculations module using the integration of linear scheduling method (LSM) and critical chain project management (CCPM), cost calculations module that considers direct and indirect

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Elbeltagi, Emad, Mohammed Ammar, Haytham Sanad, and Moustafa Kassab. "Overall multiobjective optimization of construction projects scheduling using particle swarm." Engineering, Construction and Architectural Management 23, no. 3 (2016): 265–82. http://dx.doi.org/10.1108/ecam-11-2014-0135.

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Purpose – Developing an optimized project schedule that considers all decision criteria represents a challenge for project managers. The purpose of this paper is to provide a multi-objectives overall optimization model for project scheduling considering time, cost, resources, and cash flow. This development aims to overcome the limitations of optimizing each objective at once resulting of non-overall optimized schedule. Design/methodology/approach – In this paper, a multi-objectives overall optimization model for project scheduling is developed using particle swarm optimization with a new evol

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Singh, Jyoti, and Chimay J. Anumba. "Real-time pipe system installation schedule generation and optimization using artificial intelligence and heuristic techniques." Journal of Information Technology in Construction 27 (February 23, 2022): 173–90. http://dx.doi.org/10.36680/j.itcon.2022.009.

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Infrastructure systems in the United States are aging and considerable investment is needed to renew and replace a significant proportion of the existing systems. Piping systems, which are used in many infrastructure systems such as the distribution networks for utilities – water, sewage, gas, oil, etc., are very important in this regard. Real time scheduling is an important and necessary task in the planning and execution of construction projects. This is of particular importance in the installation of pipe systems, for which it is time consuming to plan and coordinate between team members th

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Kulejewski, Janusz, Nabi Ibadov, Jerzy Rosłon, and Jacek Zawistowski. "Cash Flow Optimization for Renewable Energy Construction Projects with a New Approach to Critical Chain Scheduling." Energies 14, no. 18 (2021): 5795. http://dx.doi.org/10.3390/en14185795.

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This study concerns the use of the critical chain method to schedule the construction of renewable energy facilities. The critical chain method is recognized as a useful project management tool, transforming a stochastic problem of uncertainty in activity durations into a deterministic one. However, this method has some shortcomings. There are no clear principles of grouping non-critical activities into feeding chains. Another ambiguity is sizing the feeding buffers with regard to the topology of the network model and the resulting dependencies between activities, located in different chains.

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Peng, Zhigong, Baozhong Zhang, Jiabing Cai, Zheng Wei, He Chen, and Yu Liu. "Optimization of Spring Wheat Irrigation Schedule in Shallow Groundwater Area of Jiefangzha Region in Hetao Irrigation District." Water 11, no. 12 (2019): 2627. http://dx.doi.org/10.3390/w11122627.

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Due to the large spatial variation of groundwater depth, it is very difficult to determine suitable irrigation schedules for crops in shallow groundwater area. A zoning optimization method of irrigation schedule is proposed here, which can solve the problem of the connection between suitable irrigation schedules and different groundwater depths in shallow groundwater areas. The main results include: (1) Taking the annual mean groundwater depth 2.5 m as the dividing line, the shallow groundwater areas were categorized into two irrigation schedule zones. (2) On the principle of maximizing the yi

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Riantini, Leni Sagita, Mohammad Ichsan, Bambang Trigunarsyah, Ayomi Dita Rarasati, Nuraziz Handika, and Chrys Adrian Lolo. "Optimization of completion schedule forecasting in case study of double-double track development project (Package A) using the probabilistic pert method." Journal of Infrastructure, Policy and Development 8, no. 9 (2024): 7798. http://dx.doi.org/10.24294/jipd.v8i9.7798.

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This study aims to identify the risk factors causing the delay in the completion schedule and to determine an optimization strategy for more accurate completion schedule prediction. A validated questionnaire has been used to calculate a risk rating using the analytical hierarchy process (AHP) method, and a Monte Carlo simulation on @RISK 8.2 software was employed to obtain a more accurate prediction of project completion schedules. The study revealed that the dominant risk factors causing project delays are coordination with stakeholders and changes in the scope of work/design review. In addit

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Abuwarda, Zinab, and Tarek Hegazy. "Multi-dimensional optimization model for schedule fast-tracking without over-stressing construction workers." Canadian Journal of Civil Engineering 46, no. 12 (2019): 1160–73. http://dx.doi.org/10.1139/cjce-2018-0544.

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Fast-tracking is an important process to speed the delivery of construction projects. To support optimum fast-tracking decisions, this paper introduces a generic schedule optimization framework that integrates four schedule acceleration dimensions: linear activity crashing; discrete activity modes of execution; alternative network paths; and flexible activity overlapping. Because excessive schedule compression can lead to space congestion and overstressed workers, the optimization formulation uses specific variables and constraints to prevent simultaneous use of overlapping and crashing at the

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Irpiena, Resela, Ratna Setyawardani Alifen, and Herry Pintardi Chandra. "Model Proyeksi Dan Optimalisasi Cash Flow Multi Proyek." Dimensi Utama Teknik Sipil 3, no. 2 (2016): 1–8. http://dx.doi.org/10.9744/duts.3.2.1-8.

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This study aims to create an integrated system that has the ability to project the schedule and cash flow of a multi project situation for construction companies, while optimizing them so that a more efficient schedule and financial planning is achieved. In this study, an efficient construction planning refers to a schedule combination that generates a cash flow with minimum overdraft for the company.This study focuses on utilizing floats from non-critical activities in initial or as-planned schedule. Iteration on the floats is done with evolutionary algorithm optimization method using project

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Zhao, Juan, and Yao Xiao. "Application Research of Critical Chain Technology in Project Portfolio Schedule Management." Journal of Engineering System 2, no. 1 (2024): 51–58. http://dx.doi.org/10.62517/jes.202402110.

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The study proposes a schedule optimization management framework for warehouse construction project clusters, driven by the goal of enhancing the efficiency and quality of the engineering delivery process. With the rapid expansion trend in modern enterprises' business activities, warehouse construction projects not only grow rapidly in scale but also increase in complexity, raising the requirements for accurate project management, especially in time planning precision. The cutting-edge project management tool, Critical Chain Method, has demonstrated significant advantages in managing uncertaint

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Pavlovic, Danica. "Sensitivity analysis of airline schedule optimization (ASO) advanced model." Journal of Air Transport Studies 1, no. 2 (2010): 1–26. http://dx.doi.org/10.38008/jats.v1i2.107.

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The ASO model provides a proposal for a new flight schedule, in situations when a carrier’s flight scheduled is disrupted, and which would minimize the negative effects of the disruption. The objective function of the model is a mathematical formulation of the company’s goals and preferences, where all assumptions and operational constraints must be satisfied. The disruption costs are given in weighted coefficients which present the penalties that can be changed by the dispatcher. One of the goals was to test to what degree the generated solutions are sensitive to changes in penalty values.

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Yamamoto, Rei, and Hiroshi Konno. "REBALANCE SCHEDULE OPTIMIZATION OF A LARGE SCALE PORTFOLIO UNDER TRANSACTION COST." Journal of the Operations Research Society of Japan 56, no. 1 (2013): 26–37. http://dx.doi.org/10.15807/jorsj.56.26.

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Mezentsev, Yu A., Yu L. Korotkova, and I. V. Estraich. "An Efficient Algorithm for Solving the Applied Problem Scheduling Optimization of a Parallel-Sequential System." Informacionnye Tehnologii 27, no. 12 (2021): 642–50. http://dx.doi.org/10.17587/it.27.642-650.

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The problem of optimal regulation of airline fleet schedules by reassigning aircraft to flights is considered. The optimal regulation of schedules is to create or change them in such a way that minimizes system losses due to current violations. As an estimate of losses, the total deviation of the adjusted schedule from the spetified departure schedules of aircraft is used. It is shown that the described technological system belongs to the category of parallel-sequential systems. Accordingly, the considered system control problem is NP-hard and does not have effective algorithms for exact solut

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Li, Han Wen, and Fu Zhou Luo. "Optimization for Limited Resource Schedule in Public Construction Project." Applied Mechanics and Materials 457-458 (October 2013): 1639–43. http://dx.doi.org/10.4028/www.scientific.net/amm.457-458.1639.

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The optimization of scheduling is an important aspect of the construction project plan, the paper proposes applying improved ant colony optimization to solve the public construction projects scheduling optimization problem under limited resource condition and constructs the mathematical model of the project construction schedule optimization. Further verify the validity of the model and the improved ant colony optimization on the schedule of the optimization problem solving has universal applicability.

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