scholarly journals An Efficient Satellite Resource Cooperative Scheduling Method on Spatial Information Networks

Mathematics ◽  
2021 ◽  
Vol 9 (24) ◽  
pp. 3293
Author(s):  
Huilong Fan ◽  
Zhan Yang ◽  
Shimin Wu ◽  
Xi Zhang ◽  
Jun Long ◽  
...  
Keyword(s):  
Graph Theory ◽  
Spatial Information ◽  
Resource Scheduling ◽  
Maximum Flow ◽  
Resource Planning ◽  
Information Networks ◽  
Planning Problem ◽  
Scheduling Problems ◽  
Time Consumption ◽  
Resource Request

To overcome the low timeliness of resource scheduling problems in spatial information networks, we propose a method based on a dynamic reconstruction of resource request queues and the autonomous coordinated scheduling of resources. First, we construct a small satellite network and combine the graph maximum flow theory to solve the link resource planning problem during inter-satellite data transmission. In addition, we design a multi-satellite resource scheduling algorithm with minimal time consumption based on graph theory. The algorithm is based on graph theory to reallocate the resource request queue to satellites with idle processing resources. Finally, we simulate the efficient resource scheduling capability in the spatial information network and empirically compare our approaches against two representative swarm intelligence baseline approaches and show that our approach has significant advantages in terms of performance and time consumption during resource scheduling.

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

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.

scholarly journals A Model for Urban Environment and Resource Planning Based on Green GDP Accounting System

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Linyu Xu ◽  
Bing Yu ◽  
Wencong Yue ◽  
Xiaodong Xie
Keyword(s):  
Urban Environment ◽  
Energy Use ◽  
Resource Planning ◽  
Planning Problem ◽  
Accounting System ◽  
Analytic Hierarchy ◽  
Urban Economic Development ◽  
Long Run ◽  
Green Gdp ◽  
Key Factor

The urban environment and resources are currently on course that is unsustainable in the long run due to excessive human pursuit of economic goals. Thus, it is very important to develop a model to analyse the relationship between urban economic development and environmental resource protection during the process of rapid urbanisation. This paper proposed a model to identify the key factors in urban environment and resource regulation based on a green GDP accounting system, which consisted of four parts: economy, society, resource, and environment. In this model, the analytic hierarchy process (AHP) method and a modified Pearl curve model were combined to allow for dynamic evaluation, with higher green GDP value as the planning target. The model was applied to the environmental and resource planning problem of Wuyishan City, and the results showed that energy use was a key factor that influenced the urban environment and resource development. Biodiversity and air quality were the most sensitive factors that influenced the value of green GDP in the city. According to the analysis, the urban environment and resource planning could be improved for promoting sustainable development in Wuyishan City.

Graph Theory, Scheduling Problems, and Its Modern Applications

2021 ◽  
Author(s):  
Gavriel Owens ◽  
Javokhir Khusanov ◽  
Adilet Zholdoshov ◽  
Azamat Dzholbunov
Keyword(s):  
Graph Theory ◽  
Scheduling Problems

scholarly journals High resolution remote sensing image segmentation based on graph theory and fractal net evolution approach

2015 ◽  
Vol XL-7/W4 ◽  
pp. 197-201 ◽  
Author(s):  
Y. Yang ◽  
H. T. Li ◽  
Y. S. Han ◽  
H. Y. Gu
Keyword(s):  
Remote Sensing ◽  
Image Segmentation ◽  
Graph Theory ◽  
High Resolution ◽  
Spatial Information ◽  
Remote Sensing Image ◽  
Sensing Applications ◽  
Initial Object ◽  
Object Layer ◽  
Evolution Approach

Image segmentation is the foundation of further object-oriented image analysis, understanding and recognition. It is one of the key technologies in high resolution remote sensing applications. In this paper, a new fast image segmentation algorithm for high resolution remote sensing imagery is proposed, which is based on graph theory and fractal net evolution approach (FNEA). Firstly, an image is modelled as a weighted undirected graph, where nodes correspond to pixels, and edges connect adjacent pixels. An initial object layer can be obtained efficiently from graph-based segmentation, which runs in time nearly linear in the number of image pixels. Then FNEA starts with the initial object layer and a pairwise merge of its neighbour object with the aim to minimize the resulting summed heterogeneity. Furthermore, according to the character of different features in high resolution remote sensing image, three different merging criterions for image objects based on spectral and spatial information are adopted. Finally, compared with the commercial remote sensing software eCognition, the experimental results demonstrate that the efficiency of the algorithm has significantly improved, and the result can maintain good feature boundaries.

A New Decision Support System for Optimal Integrated Project Scheduling and Resource Planning

2021 ◽  
pp. 1367-1383
Author(s):  
Amir Ahrari ◽  
Ali Haghani
Keyword(s):  
Resource Allocation ◽  
Project Scheduling ◽  
Efficient Solution ◽  
Practical Problem ◽  
Mathematical Formulation ◽  
Optimal Solution ◽  
Resource Planning ◽  
Scheduling Problems ◽  
Activity Scheduling ◽  
Integrated Project

Two scheduling practices are commonly used depending on the availability of resources. When resources are not expensive, activities are scheduled and then resources are allocated until the available resources are exhausted. Then, iterative adjustments are applied to the resource allocation plan and the activities sequence to reach a feasible solution. Conversely, when expensive resources are involved, a resource allocation plan based on the economics of the resource is established and then activities are scheduled accordingly. However, Resource Constrained Scheduling Problems (RCSP) are not solved efficiently with either of these approaches. To find the optimal solution, activity scheduling and resource allocation should be formulated as an integrated optimization problem. Such models become numerically cumbersome for practical size problems and difficult to solve. In this article, a novel mathematical formulation and an efficient solution algorithm are proposed for solving RCSPs. Then, this framework is used for solving a practical problem in the context of the construction industry.

scholarly journals Efficient Solution Approach to Maximum Flow Evacuation Planning Problem without Flow Conservation Aspect

2018 ◽  
Vol 13 (1) ◽  
pp. 108-116
Author(s):  
Phanindra Prasad Bhandari ◽  
Shree Ram Khadka
Keyword(s):  
Network Flow ◽  
Efficient Solution ◽  
Maximum Flow ◽  
Evacuation Planning ◽  
Planning Problem ◽  
Intermediate Node ◽  
Solution Approach ◽  
Solution Strategies ◽  
Source Sink ◽  
Flow Conservation

 An attempt of shifting as more people as possible and/or their logistics from a dangerous place to a safer place is an evacuation planning problem. Such problems modeled on network have been extensively studied and the various efficient solution procedures have been established. The solution strategies for these problems are based on source-sink path augmentation and the flow function satisfies the flow conservation at each intermediate node. Besides this, the network flow problem in which flow may not be conserved at node necessarily could also be used to model the evacuation planning problem. This paper proposes a model for maximum flow evacuation planning problem on a single-source-single-sink static network with integral arc capacities with holding capability of evacuees in the temporary shelter at intermediate nodes and extends the model into the dynamic case. Journal of the Institute of Engineering, 2017, 13(1): 108-116

scholarly journals Flow Improvement in Evacuation Planning with Budget Constrained Switching Costs

2020 ◽  
Vol 2020 ◽  
pp. 1-10 ◽  
Author(s):  
Ram Chandra Dhungana ◽  
Tanka Nath Dhamala
Keyword(s):  
Network Flow ◽  
Large Scale ◽  
Maximum Flow ◽  
Evacuation Planning ◽  
Solution Technique ◽  
Planning Problem ◽  
Constrained Problems ◽  
Full Capacity ◽  
Evacuation Plan ◽  
Flow Improvement

Many large-scale natural and human-created disasters have drawn the attention of researchers towards the solutions of evacuation planning problems and their applications. The main focus of these solution strategies is to protect the life, property, and their surroundings during the disasters. With limited resources, it is not an easy task to develop a universally accepted model to handle such issues. Among them, the budget-constrained network flow improvement approach plays significant role to evacuate the maximum number of people within the given time horizon. In this paper, we consider an evacuation planning problem that aims to shift a maximum number of evacuees from a danger area to a safe zone in limited time under the budget constraints for network modification. Different flow improvement strategies with respect to fixed switching cost will be investigated, namely, integral, rational, and either to increase the full capacity of an arc or not at all. A solution technique on static network is extended to the dynamic one. Moreover, we introduce the static and dynamic maximum flow problems with lane reversal strategy and also propose efficient algorithms for their solutions. Here, the contraflow approach reverses the direction of arcs with respect to the lane reversal costs to increase the flow value. As an implementation of an evacuation plan may demand a large cost, the solutions proposed here with budget constrained problems play important role in practice.

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