A real time kernel to support the Transputer programming model

1997 ◽  
pp. 615-623
Author(s):  
Adrian Cox ◽  
Anthony Hall
Keyword(s):  
Real Time ◽  
Programming Model

A hybrid fuzzy quantum time series and linear programming model: Special application on TAIEX index dataset

2019 ◽  
Vol 34 (25) ◽  
pp. 1950201 ◽  
Author(s):  
Pritpal Singh ◽  
Gaurav Dhiman ◽  
Sen Guo ◽  
Ritika Maini ◽  
Harsimran Kaur ◽  
...  
Keyword(s):  
Time Series ◽  
Linear Programming ◽  
Real Time ◽  
Time Series Data ◽  
Programming Model ◽  
Series Data ◽  
Quantum Model ◽  
Quantum Time ◽  
Degree Of Membership ◽  
Quantum Approach

The supremacy of quantum approach is able to provide the solutions which are not practically feasible on classical machines. This paper introduces a novel quantum model for time series data which depends on the appropriate length of intervals. In this study, the effects of these drawbacks are elaborately illustrated, and some significant measures to remove them are suggested, such as use of degree of membership along with mid-value of the interval. All these improvements signify the effective results in case of quantum time series, which are verified and validated with real-time datasets.

scholarly journals Applying a Model for Trip Assignment and Dynamic Routing of Automated Taxis with Congestion: System Performance in the City of Delft, The Netherlands

2018 ◽  
Vol 2672 (8) ◽  
pp. 588-598 ◽  
Author(s):  
Xiao Liang ◽  
Gonçalo Homem de Almeida Correia ◽  
Bart van Arem
Keyword(s):  
The Netherlands ◽  
Real Time ◽  
Traffic Congestion ◽  
Programming Model ◽  
Profit Maximization ◽  
The Real ◽  
Real Size ◽  
The Impact ◽  
The City

This paper proposes a method of assigning trips to automated taxis (ATs) and designing the routes of those vehicles in an urban road network, and also considering the traffic congestion caused by this dynamic responsive service. The system is envisioned to provide a seamless door-to-door service within a city area for all passenger origins and destinations. An integer programming model is proposed to define the routing of the vehicles according to a profit maximization function, depending on the dynamic travel times, which varies with the ATs’ flow. This will be especially important when the number of automated vehicles (AVs) circulating on the roads is high enough that their routing will cause delays. This system should be able to serve not only the reserved travel requests, but also some real-time requests. A rolling horizon scheme is used to divide one day into several periods in which both the real-time and the booked demand will be considered together. The model was applied to the real size case study city of Delft, the Netherlands. The results allow assessing of the impact of the ATs movements on traffic congestion and the profitability of the system. From this case-study, it is possible to conclude that taking into account the effect of the vehicle flows on travel time leads to changes in the system profit, the satisfied percentage and the driving distance of the vehicles, which highlights the importance of this type of model in the assessment of the operational effects of ATs in the future.

IoT-based real time intelligent routing for emergent crowd evacuation

2019 ◽  
Vol 37 (3) ◽  
pp. 604-624
Author(s):  
Yanlan Mei ◽  
Ping Gui ◽  
Xianfeng Luo ◽  
Benbu Liang ◽  
Liuliu Fu ◽  
...  
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Programming Model ◽  
Emergency Evacuation ◽  
Guidance System ◽  
Programming Approach ◽  
Metro Station ◽  
Content Type ◽  
Crowd Evacuation ◽  
Evacuation Route

Purpose The purpose of this paper is to take advantage of Internet of Things (IoT) for intelligent route programming of crowd emergency evacuation in metro station. It is a novel approach to ensure the crowd safety and reduce the casualties in the emergency context. An evacuation route programming model is constructed to select a suitable evacuation route and support the emergency decision maker of metro station. Design/methodology/approach The IoT technology is employed to collect and screen information, and to construct an expert decision model to support the metro station manager to make decision. As a feasible way to solve the multiple criteria decision-making problem, an improved multi-attributive border approximation area comparison (MABAC) approach is introduced. Findings The case study indicates that the model provides valuable suggestions for evacuation route programming and offers practical support for the design of an evacuation route guidance system. Moreover, IoT plays an important role in the process of intelligent route programming of crowd emergency evacuation in metro station. A library has similar structure and crowd characteristics of a metro station, thus the intelligent route programming approach can be applied to the library crowd evacuation. Originality/value The highlights of this paper are listed as followings: the accuracy and accessibility of the metro station’s real-time information are improved by integrating IoT technology with the intelligent route programming of crowd emergency evacuation. An improved MABAC approach is introduced to the expert support model. It promotes the applicability and reliability of decision making for emergency evacuation route selection in metro station. It is a novel way to combine the decision-making methods with practice.

Real-time system development: The programming model of MARS

2002 ◽  
Author(s):  
H. Kopetz ◽  
G. Fohler ◽  
G. Grunsteidl ◽  
H. Kantz ◽  
G. Pospischil ◽  
...  
Keyword(s):  
Real Time ◽  
Programming Model ◽  
System Development ◽  
Time System ◽  
Real Time System

A Dual Programming Model for Distributed Real-Time Java

2011 ◽  
Vol 7 (4) ◽  
pp. 750-758 ◽  
Author(s):  
P. Basanta-Val ◽  
M. Garcia-Valls ◽  
I. Estevez-Ayres
Keyword(s):  
Real Time ◽  
Programming Model ◽  
Dual Programming

scholarly journals A Multi-Objective Mathematical Model for Real-Time Employee Assignment in the Service Industry

2021 ◽  
Author(s):  
Gercek Budak ◽  
Xin Chen
Keyword(s):  
Mathematical Model ◽  
Real Time ◽  
Customer Service ◽  
Service Industry ◽  
Programming Model ◽  
Manufacturing Sector ◽  
Mixed Integer ◽  
Multi Objective ◽  
Service Rates ◽  
The Mathematical Model

Abstract The American economy has shifted toward services since the 1980s. The service industry is an important part of economy and is growing quickly in the last three decades. It is more human-capital intensive than the manufacturing sector and there is a shortage of highly-skilled workforce. One solution to this problem is to improve the efficiency through optimization. Because demand in the service industry changes constantly, it is a great challenge to determine the number of employees and their tasks to improve customer service while reducing cost. This article develops a multi-objective mixed-integer linear programming model to dynamically assign employees to different workstations in real time. A case study of the model is solved in less than one second and its pareto optimal solutions determine the number of employees who are assigned to each workstation and the expected customer service times. The mathematical model is robust and provides optimal employee assignment and service rates for workstations in many situations.

Sign in / Sign up

Export Citation Format

Share Document