1,720,979 research outputs found
Comparing Lagrangian-based distributed algorithms for parallel machine scheduling problems
No full textIn this paper Lagrangian-based distributed algorithms for scheduling jobs on unrelated parallel machines are presented. In these algorithms, the scheduling process is the result of a cooperation process among several Decision Makers (DMs). DMs have a local knowledge of the system, and the possibility to decide which type of information to exchange each other. Our focus is to investigate the performance of different algorithms based on different knowledge degrees of the parallel machine system. The implementation issues and the effectiveness of the algorithms are analysed via simulation, in which problem instances with job dynamic arrivals are also considered. Copyright © 2009, Inderscience Publishers
Situation awareness in critical infrastructures
No full textCritical infrastructure (CI) protection and situation awareness are relevant topics in critical system domain. These issues go far beyond the academic world involving very often the national security framework. In this contribution, a review of the most attractive approaches proposed for addressing the situation awareness problems is presented. Most of the proposed approaches are based on multi-sensor data fusion, since the awareness is achieved by building a scenario using data provided by sensors spread into the systems. Humans are supposed to interact with the system, but only a few models are able to include their intervention. The review analysis is performed by considering models, architectures, and techniques adopted in each system and by highlighting their effectiveness and drawbacks. Finally an example in the field of air traffic management is presented. © 2014 Inderscience Enterprises Ltd
The global optimization of signal settings and traffic assignment combined problem: A comparison between algorithms
No full textThe increasing vehicular traffic on urban road in network demands effective measure of traffic control on road network, especially at the intersection, where turning movement of vehicle and mixed traffic creates congestion. In congested parts of the cities, traffic control at road intersection is the most efficient method. The Traffic Signal Synchronization is a traffic engineering technique of matching the green light times for a series of intersections to enable the maximum number of vehicles to pass through, thereby reducing stops and delays experienced by motorists. The principal objective of Traffic Signal Synchronization at intersection is to clear maximum number of vehicles through the intersection in a given length and time with least number of accidents, at maximum safe speed and with minimum delay. Synchronizing traffic signals ensures a better flow of traffic and minimizes gas consumption and pollutant emissions. In this paper, we apply different approaches to minimize the total travel time on the network. The Surrogate Method (SM), the Projected Gradient Algorithm (PGA), the Particle Swarm Optimization (PSO) and the Genetic Algorithm (GA) are developed for the Global Optimization of Signal Settings and Traffic Assignment combined problem. Numerical experiments on real test network are reported
A planning and routing model for the integrated supply chain management
No full textThe supply of complex products often involves the assembly of other products, components or sub-assemblies. Furthermore, these sub-assemblies may be produced by different suppliers. As a result, the specification of the assembly process for the final product contains relationship between multiple supply chain components, including business entities, manufacturing processes, products, and parts. This specification, involving the coordination and arrangement of components production to support final product assembly, is referred to as a supply chain planning and routing. An optimization model is proposed to deals with the routing problem considering constraints on the suppliers production capacity and minimizing the transportation costs
Optimization of airport check-in service quality focused on operational costs and passengers’ satisfaction
No full textPassengers’ requirements in relation to the Airport Service Quality is rapidly increasing and forcing companies and airport management to improve the services performances. It is clear that this enhancement can not overlook the implication of competitive issues and economic concerns. In this paper the authors deal with the optimization of the check-in area management in the international airport of Lisbon. The proposed bi-criteria objective function minimizes the operational costs plus the costs measuring the passengers’ discomfort in terms of waiting time in line. The quality of the supplied check-in service is measured and mapped into the Levels of Service system standardized by the International Air Transport Association. The type of passengers and their stochastic behavior and preferences are simulated by a discrete event model. The operational costs and the passengers’ satisfaction are optimized by an algorithm based on the Surrogate Method, the performance of which are compared to those of a greedy heuristic and of a genetic algorithm
A macroscopic model with the advantages of microscopic model: A review of Cell Transmission Model's extensions for urban traffic networks
No full textThis paper reports a review of the extensions and application of the Cell Transmission Model (CTM). Those extensions are models able to simulate complex urban traffic dynamics with all the advantages of macroscopic and microscopic urban traffic model. Over the past few years researchers have been trying to increase the level of detail by extending CTM and introducing new formulations to improve the application of the model in urban traffic. The authors classified the papers while taking into consideration all those factors characterizing the urban traffic, arterial and intersection traffic flow in particular. One of the primary goals of transport research is to develop a general framework of urban traffic networks that might be applied from a realistic point of view. Recent studies about traffic simulations have shown that, among various macroscopic simulation models, the CTM has the potential to achieve this objective. We have also reported our model the CTM_UT that improves the CTM for Urban Traffic. We believe that it is possible to apply this model to ITS application, hence increase the accuracy of the macroscopic model while maintaining the computational advantages and provide an accurate prediction of travel time approach
Cooperative and competitive negotiation in a Supply Chain Model
No full textWe present a negotiation paradigm for a simple supply chain (SC) model, to improve the performances in terms of bullwhip effect reduction, under a cooperative and a competitive scenario. In the case of a single frequency perturbation in the nominal demand, analytical results showed that cooperation among the sites is beneficial for the SC performances. In the case of multiple frequency perturbations this has been described through numerical examples, which confirm the analytical findings of the single frequency case
Simulation of a schedule-based mass vaccination clinic
No full textThe insurgence of the COVID-19 pandemic has compelled many countries to set up vaccination clinics to carry out mass vaccination campaigns. Though sizing a clinic impacts both costs and service quality, and costs must be scaled up nationwide, those clinics and their staffing have often been put into service without a proper design phase. In this paper, we propose a simulator that allows us to analyse a vaccination clinic's performance and optimise its capacity and staff level, considering typical schedule-based operations. Though a trade-off is unavoidable between cost and service quality, the latter being represented by the throughput time, we show that we can achieve a significant increase in the efficient use of nurses' time with a small sacrifice in service quality, i.e., a small increase of the throughput time
Decision support methodologies and day-ahead optimization for smart building energy management in a dynamic pricing scenario
Full text linkNowadays identifying techniques aimed at a rational use of electric power has become even more important than the production of energy itself. This is caused by different factors, as the progressive saturation of the electricity grid, which is increasingly subject to connection requests, mainly due to the development of plants which exploit renewable energy sources. This work suggests a new approach based on the combination of the optimizer and the simulator developed in the MATLAB/Simulink environment, in order to reduce the energy costs in buildings during the summer while taking into consideration the user comfort. The electrical consumption of the entire building is taken into consideration is here examined with the aim of applying an air-conditioning system. The goal is to find, the day before, which is the optimal hourly scheduling of the control variables that must be applied the next day, taking into consideration all external conditions; weather conditions and the hourly energy price. In order to achieve this objective, the control variables, that have been changed, are the room temperature set points and the flow water temperature set point. As required by the UNI EN ISO 7730:2006 standard, comfort measurement is calculated by PPD (Predicted Percentage of Dissatisfied) index. Different scenarios are investigated and two optimization algorithms are compared. The results show that there is an average of 10−28% potential cost saving, while maintaining a high level of comfort (PPD ≤ 12). The study is carried out by simulating a real office building in Italy, and the comparisons are shown regarding the actual settings applied to it
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