An uncertain model for RCPSP with solution robustness focusing on logistics project schedule

Marine structures are inevitably influenced by parametric perturbations as well as multiple external loadings. Among these loadings, earthquake is generally more destructive and unpredictable than others. It is significant to develop effective active control schemes to guarantee the safety, stability, and integrity of marine structures subject to earthquakes and parametric perturbations. In this paper, the problem of networked [Formula: see text] robust damping control is addressed to stabilize a marine structure subject to earthquakes. First, in consideration of perturbations of the structure parameters, an uncertain model of the networked marine structure under earthquakes is presented. Second, a robust networked [Formula: see text] control scheme is presented to suppress seismic responses of the structure. By using stability theory of time-delay systems, several sufficient conditions on robust stability of the networked marine structure system are obtained, and the linear matrix inequality methods are utilized to solve the gain matrix of the controller. Finally, simulation indicates that compared with the traditional robust [Formula: see text] control and the proposed networked [Formula: see text] control, the seismic responses amplitudes of the marine structure under the two controllers are almost the same, while the latter is more economic than the former.

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Scheduling Optimization of Prefabricated Construction Projects by Genetic Algorithm

Applied Sciences ◽

10.3390/app11125531 ◽

2021 ◽

Vol 11 (12) ◽

pp. 5531

Author(s):

Linlin Xie ◽

Yajiao Chen ◽

Ruidong Chang

Keyword(s):

Project Scheduling ◽

Construction Projects ◽

Resource Constraints ◽

Construction Project ◽

Engineering Application ◽

Project Schedule ◽

Scheduling Optimization ◽

Implementation Method ◽

Traditional Construction ◽

Construction Project Scheduling

Prefabricated buildings are the direction of the future development of the construction industry and have received widespread attention. The effective execution of prefabricated construction project scheduling should consider resource constraints and the supply arrangement of prefabricated components. However, the traditional construction resource-constrained project scheduling implementation method cannot simultaneously consider the characteristics of the linkage between component production and on-site assembly construction. It cannot also fully adapt to the scheduling implementation method of the prefabricated construction projects. It is difficult to work out a reasonable project schedule and resource allocation table. In order to determine the relevant schedule parameters that can reflect the actual construction situation of the prefabricated building and meet the scheduling requirements of the prefabricated project, this study proposes a prefabricated construction project scheduling model that considers project resource constraints and prefabricated component supply constraints. Additionally, it improves the design of traditional genetic algorithms (GAs). Research results of the experimental calculation and engineering application show that the proposed project scheduling optimization model and GA are effective and practical, which can help project managers in effectively formulating prefabricated construction project scheduling plans, reasonably allocating resources, reducing completion time, and improving project performance.

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A Critical Design Structure Method for Project Schedule Development under Rework Risks

Sustainability ◽

10.3390/su11247229 ◽

2019 ◽

Vol 11 (24) ◽

pp. 7229

Author(s):

Guofeng Ma ◽

Jianyao Jia ◽

Tiancheng Zhu ◽

Shan Jiang

Keyword(s):

Resource Constraints ◽

Project Schedule ◽

Management Tools ◽

Simulation Methodology ◽

Schedule Management ◽

Critical Design ◽

Design Structure ◽

Activity Sequence ◽

Impact Area ◽

Critical Chain

In order to overcome the difficulty in quantifying rework by traditional project schedule management tools, this study proposes an innovative method, namely improved Critical Chain Design Structure Matrix (ICCDSM). From the perspective of information flow, the authors firstly make assumptions on activity parameters and interactions between activities. After that, a genetic algorithm is employed to reorder the activity sequence, and a banding algorithm with consideration of resource constraints is used to identify concurrent activities. Then potential criticality is proposed to measure the importance of each activity, and the rework impact area is implicated to indicate potential rework windows. Next, two methods for calculating project buffer are employed. A simulation methodology is used to verify the proposed method. The simulation results illustrate that the ICCDSM method is capable of quantifying and visualizing rework and its impact, decreases iterations, and improves the completion probability. In this vein, this study provides a novel framework for rework management, which offers some insights for researchers and managers.

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Integrating Schedule Risk Analysis with Multi-Skilled Resource Scheduling to Improve Resource-Constrained Project Scheduling Problems

Applied Sciences ◽

10.3390/app11020650 ◽

2021 ◽

Vol 11 (2) ◽

pp. 650

Author(s):

Muritala Adebayo Isah ◽

Byung-Soo Kim

Keyword(s):

Risk Analysis ◽

Project Scheduling ◽

Resource Scheduling ◽

Scheduling Problems ◽

Project Schedule ◽

Risk And Uncertainty ◽

Resource Constrained ◽

Resource Constrained Project Scheduling ◽

Schedule Risk ◽

Schedule Risk Analysis

Construction projects are planned in a complex and dynamic environment characterized by high risks and uncertainties amidst resource constraints. Assessing construction schedule risk facilitates informed decision-making, especially in a resource-constrained situation, and allows proactive actions to be taken so that project objectives are not jeopardized. This study presents a stochastic multiskilled resource scheduling (SMSRS) model for resource-constrained project scheduling problems (RCSPSP) considering the impact of risk and uncertainty on activity durations. The SMSRS model was developed by integrating a schedule risk analysis (SRA) model (developed in MS Excel) with an existing multiskilled resource scheduling (MSRS) algorithm for the development of a feasible and realistic schedule. The computational experiment carried out on three case projects using the proposed SMSRS model revealed an average percentage deviation of 10.50%, indicating the inherent risk and uncertainty in activity durations of the project schedule. The core contribution of the proposed SMSRS model is that it: (1) presents project practitioners with a simple tool for assessing the risks and uncertainty associated with resource-constrained project schedules so that necessary response actions can be taken to ensure project success; (2) provides the small-scale construction businesses with an affordable tool for evaluating schedule risk and developing a feasible and realistic project schedule.

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The Optimization of Project Time-Cost Based on Particle Swarm Optimization Algorithm

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.791-793.1423 ◽

2013 ◽

Vol 791-793 ◽

pp. 1423-1426

Author(s):

Hai Min Wei ◽

Rong Guang Liu

Keyword(s):

Particle Swarm Optimization ◽

Particle Swarm Optimization Algorithm ◽

Cost Optimization ◽

Particle Swarm ◽

Implementation Process ◽

Pso Algorithm ◽

Project Schedule ◽

Swarm Optimization ◽

Schedule Optimization ◽

Schedule Management

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 swarm optimization (PSO) algorithm and its parameters which have effect on the algorithm:Particle swarm optimization (PSO) algorithm is presented in the time limited project and the application of a cost optimization.

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A fault-tolerant control scheme within adaptive disturbance observer for hypersonic vehicle

Proceedings of the Institution of Mechanical Engineers Part G Journal of Aerospace Engineering ◽

10.1177/0954410017746702 ◽

2017 ◽

Vol 233 (3) ◽

pp. 1071-1088 ◽

Cited By ~ 3

Author(s):

Jun Zhou ◽

Jing Chang ◽

Zongyi Guo

Keyword(s):

Disturbance Observer ◽

Fault Tolerant ◽

Sliding Mode ◽

Fault Tolerant Control ◽

Lyapunov Theory ◽

Sliding Mode Controller ◽

Performance Guarantees ◽

Uncertain Model ◽

Control Scheme ◽

And Performance

The paper describes the design of a fault-tolerant control scheme for an uncertain model of a hypersonic reentry vehicle subject to actuator faults. In order to improve superior transient performances for state tracking, the proposed method relies on a back-stepping sliding mode controller combined with an adaptive disturbance observer and a reference vector generator. This structure allows for a faster response and reduces the overshoots compared to linear conventional disturbance observers based sliding mode controller. Robust stability and performance guarantees of the overall closed-loop system are obtained using Lyapunov theory. Finally, numerical simulations results illustrate the effectiveness of the proposed technique.

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