scholarly journals Share-of-Surplus Product Line Optimisation with Price Levels

2014 ◽  
Vol 2014 ◽  
pp. 1-8
Author(s):  
X. G. Luo ◽  
Z. C. Zhang ◽  
C. K. Kwong ◽  
J. F. Tang
Keyword(s):  
Planning Process ◽  
Early Stage ◽  
Computation Time ◽  
Product Line ◽  
Nonlinear Integer Programming ◽  
Mixed Integer ◽  
Decision Variable ◽  
Price Levels ◽  
Linearisation Techniques ◽  
Optimisation Model

Kraus and Yano (2003) established the share-of-surplus product line optimisation model and developed a heuristic procedure for this nonlinear mixed-integer optimisation model. In their model, price of a product is defined as a continuous decision variable. However, because product line optimisation is a planning process in the early stage of product development, pricing decisions usually are not very precise. In this research, a nonlinear integer programming share-of-surplus product line optimization model that allows the selection of candidate price levels for products is established. The model is further transformed into an equivalent linear mixed-integer optimisation model by applying linearisation techniques. Experimental results in different market scenarios show that the computation time of the transformed model is much less than that of the original model.

A mixed integer optimisation model for data classification

2009 ◽  
Vol 56 (4) ◽  
pp. 1205-1215 ◽  
Author(s):  
Gang Xu ◽  
Lazaros G. Papageorgiou
Keyword(s):  
Data Classification ◽  
Mixed Integer ◽  
Optimisation Model

Arcades City: Early-Modern City Planning Practice of Wuzhou

2014 ◽  
Vol 641-642 ◽  
pp. 616-619
Author(s):  
Ji Li ◽  
Bai Hao Li ◽  
Li Lin
Keyword(s):  
Early Modern ◽  
City Planning ◽  
Planning Process ◽  
Early Stage ◽  
Road Construction ◽  
Urban Morphology ◽  
Planning Theory ◽  
Modern City ◽  
The Road ◽  
Historic City

With regard to planning theory and practical construction of Early-modern City Planning in Wuzhou, the paper discusses the historic city regeneration was adhere to old city structure and regional resource at early stage, and new planning refer to technology of ideal cities in Europe and America later. It also analyzes the urban morphology for the "Road Construction→Historic City Renovation→Experimental Regional Planning" process, summarizes the activities of Wuzhou early-modern city planning and construction has “Arcades City” characteristic.

Computer-assisted Diagnosis for Early Stage Pleural Mesothelioma

2007 ◽  
Vol 46 (03) ◽  
pp. 324-331 ◽  
Author(s):  
P. Jäger ◽  
S. Vogel ◽  
A. Knepper ◽  
T. Kraus ◽  
T. Aach ◽  
...  
Keyword(s):  
Early Stage ◽  
Computation Time ◽  
Hounsfield Unit ◽  
Computer Assisted ◽  
Clinical Test ◽  
Pleural Mesothelioma ◽  
Data Sets ◽  
Data Set ◽  
Average Computation Time ◽  
Ct Data

Summary Objectives: Pleural thickenings as biomarker of exposure to asbestos may evolve into malignant pleural mesothelioma. Foritsearly stage, pleurectomy with perioperative treatment can reduce morbidity and mortality. The diagnosis is based on a visual investigation of CT images, which is a time-consuming and subjective procedure. Our aim is to develop an automatic image processing approach to detect and quantitatively assess pleural thickenings. Methods: We first segment the lung areas, and identify the pleural contours. A convexity model is then used together with a Hounsfield unit threshold to detect pleural thickenings. The assessment of the detected pleural thickenings is based on a spline-based model of the healthy pleura. Results: Tests were carried out on 14 data sets from three patients. In all cases, pleural contours were reliably identified, and pleural thickenings detected. PC-based Computation times were 85 min for a data set of 716 slices, 35 min for 401 slices, and 4 min for 75 slices, resulting in an average computation time of about 5.2 s per slice. Visualizations of pleurae and detected thickeningswere provided. Conclusion: Results obtained so far indicate that our approach is able to assist physicians in the tedious task of finding and quantifying pleural thickenings in CT data. In the next step, our system will undergo an evaluation in a clinical test setting using routine CT data to quantifyits performance.

Provider Order Entry with Integrated Decision Support: from Academia to Industry

2003 ◽  
Vol 42 (01) ◽  
pp. 45-50 ◽  
Author(s):  
D.A. Giuse
Keyword(s):  
Decision Support ◽  
Large Scale ◽  
Planning Process ◽  
Academic Medical Center ◽  
Product Line ◽  
Commercial Product ◽  
Care Practice ◽  
Care Organization ◽  
Order Entry ◽  
Research Prototype

Summary Objectives: To describe the evolution of a provider order entry system with integrated decision support, from a research prototype to full implementation at one academic center, and finally to a commercial product. Methods: Describe the institutional environment and planning process in which the system originated. Highlight the historical evolution of the provider entry system, and analyze its system architecture and functionality. Describe the requirements for successful design and deployment both within a single health care organization and as part of a commercial product line. Results: Over a period of eight years the system evolved from a research prototype to a fully integrated order entry system in routine use on most inpatient units of a large academic medical center. Around 12,000 orders are entered every day into the computer system; 70% of those are entered directly by the responsible physician. The system embeds best-of-care practice guidelines, and is used to reduce resource utilization by limiting unnecessary testing and suggesting more effective or less costly therapeutic replacements. The system was recently acquired by a large HIS software vendor and is being rapidly implemented at numerous customer sites. Conclusions: Large-scale development or deployment of complex health information systems requires considerable organizational agreement and resources, as well as close attention to iterative system design that explicitly includes constant feedback from the user community. The transformation of such a system from a single-site success to a widely deployed product requires convergence of resources and needs.

scholarly journals Energy Versus Throughput Optimisation for Machine-to-Machine Communication

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4122
Author(s):  
Emma Fitzgerald ◽  
Michał Pióro ◽  
Artur Tomaszewski
Keyword(s):  
Mesh Networks ◽  
Numerical Study ◽  
Minimum Energy ◽  
Mixed Integer ◽  
Energy Usage ◽  
Maximum Throughput ◽  
Machine To Machine ◽  
Machine To Machine Communication ◽  
Optimisation Model ◽  
Machine Communication

We investigate the trade-off between energy usage and (packet) throughput in wireless mesh networks performing machine-to-machine communication. For this we provide a novel mixed-integer programming formulation to maximise the throughput while maintaining minimal energy usage, together with an effective price-and-branch solution algorithm based on column generation. The resulting optimisation model is the main original contribution of the presented paper. We conducted a numerical study using network examples from 10 to 40 nodes, in which periodic sensor measurements are aggregated and disseminated to actuators. In almost all cases, we were able to achieve maximum throughput and minimum energy usage simultaneously, and in those cases where this was not possible, the costs incurred in one objective in order to achieve the other were typically low. The solution times for all network sizes were of the order of seconds, showing that our optimisation model is feasible to use in practice.

scholarly journals Co-Optimized Analysis and Design of Electric and Natural Gas Infrastructures

Energies ◽  
2019 ◽  
Vol 12 (10) ◽  
pp. 2012 ◽  
Author(s):  
Santiago Lemos-Cano ◽  
James McCalley
Keyword(s):  
Natural Gas ◽  
Transmission Lines ◽  
Power Flow ◽  
Planning Process ◽  
The United States ◽  
Integrated System ◽  
Mixed Integer ◽  
Eastern Region ◽  
Analysis And Design ◽  
Expansion Planning

This paper proposes and implements a long-term deterministic capacity expansion model for the co-optimization of electric and natural gas infrastructures. It determines the required investments in generation units, transmission lines and pipelines for meeting future demands, while representing electricity and natural gas flows using DC Power Flow and Weymouth equations, respectively. A Mixed Integer Nonlinear Programming (MINLP) problem is developed, from which a linearized version is derived. A 26 node integrated gas-electric system for the Eastern Region of the United States is used to demonstrate the model’s capabilities. Results show that the model provides an accurate operational representation of the integrated system, and, therefore, enhances the expansion planning process.

scholarly journals Determining UAV Flight Trajectory for Target Recognition Using EO/IR and SAR

Sensors ◽  
2020 ◽  
Vol 20 (19) ◽  
pp. 5712
Author(s):  
Wojciech Stecz ◽  
Krzysztof Gromada
Keyword(s):  
Planning Process ◽  
Route Planning ◽  
Mixed Integer ◽  
Military Operations ◽  
Flight Trajectory ◽  
Planning Algorithm ◽  
Aerial Vehicle ◽  
Milp Model ◽  
Flight Trajectories ◽  
Synthetic Aperture Radars

The paper presents the concept of planning the optimal trajectory of fixed-wing unmanned aerial vehicle (UAV) of a short-range tactical class, whose task is to recognize a set of ground objects as a part of a reconnaissance mission. Tasks carried out by such systems are mainly associated with an aerial reconnaissance using Electro-Optical/Infrared (EO/IR) systems and Synthetic Aperture Radars (SARs) to support military operations. Execution of a professional reconnaissance of the indicated objects requires determining the UAV flight trajectory in the close neighborhood of the target, in order to collect as much interesting information as possible. The paper describes the algorithm for determining UAV flight trajectories, which is tasked with identifying the indicated objectives using the sensors specified in the order. The presence of UAV threatening objects is taken into account. The task of determining the UAV flight trajectory for recognition of the target is a component of the planning process of the tactical class UAV mission, which is also presented in the article. The problem of determining the optimal UAV trajectory has been decomposed into several subproblems: determining the reconnaissance flight method in the vicinity of the currently recognized target depending on the sensor used and the required parameters of the recognition product (photo, film, or SAR scan), determining the initial possible flight trajectory that takes into account potential UAV threats, and planning detailed flight trajectory considering the parameters of the air platform based on the maneuver planning algorithm designed for tactical class platforms. UAV route planning algorithms with time constraints imposed on the implementation of individual tasks were used to solve the task of determining UAV flight trajectories. The problem was formulated in the form of a Mixed Integer Linear Problem (MILP) model. For determining the flight path in the neighborhood of the target, the optimal control algorithm was also presented in the form of a MILP model. The determined trajectory is then corrected based on the construction algorithm for determining real UAV flight segments based on Dubin curves.

scholarly journals Drone-Based Parcel Delivery Using the Rooftops of City Buildings: Model and Solution

2020 ◽  
Vol 10 (12) ◽  
pp. 4362 ◽  
Author(s):  
Junsu Kim ◽  
Hongbin Moon ◽  
Hosang Jung
Keyword(s):  
Urban Areas ◽  
Programming Model ◽  
Computation Time ◽  
Intelligent Transportation ◽  
Mixed Integer ◽  
Operation Planning ◽  
Logistics System ◽  
Proposed Model ◽  
Optimality Gap ◽  
Good Operation

In general, the demand for delivery cannot be fulfilled efficiently due to the excessive traffic in dense urban areas. Therefore, many innovative concepts for intelligent transportation of freight have recently been developed. One of these concepts relies on drone-based parcel delivery using rooftops of city buildings. To apply drone logistics system in cities, the operation design should be adequately prepared. In this regard, a mixed integer programming model for drone operation planning and a heuristic based on block stacking are newly proposed to provide solutions. Additionally, numerical experiments with three different problem sizes are conducted to check the feasibility of the proposed model and to assess the performance of the proposed heuristic. The experimental results show that the proposed model seems to be viable and that the developed heuristic provides very good operation plans in terms of the optimality gap and the computation time.

Operational Planning Using Mixed Integer Programming

1988 ◽  
Vol 64 (6) ◽  
pp. 485-488 ◽  
Author(s):  
H. Douglas Walker ◽  
Stephen W. Preiss
Keyword(s):  
Planning Process ◽  
Cost Savings ◽  
Mathematical Structure ◽  
Timber Harvesting ◽  
Operational Planning ◽  
Mixed Integer ◽  
Forest Planning ◽  
Planning Problem ◽  
Process Data ◽  
Planning Problems

A mathematical model was constructed and used to help plan five-year timber harvesting and delivery activities from an industrially managed public forest in Ontario. Harvest systems, harvest levels, and wood flows from compartments within the forest to various mills and delivery points were scheduled to minimize costs. The mathematical structure of the model may suggest applications to related forest planning problems. The model was useful in addressing the planning problem, and model results were used within the company's planning process. Data accuracy problems precluded assessing definitively the expected cost savings resulting from model use.

Sign in / Sign up

Export Citation Format

Share Document