scholarly journals Flights Assignment Model of Multiple Airports Based on Game Theory and CDM Mechanism

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Junqiang Liu
Keyword(s):  
Game Theory ◽  
Assignment Problem ◽  
Ant Colony Algorithm ◽  
Exchange Method ◽  
Assignment Model ◽  
Airport Capacity ◽  
Proposed Model ◽  
Minimum Delay ◽  
Delay Cost ◽  
Better Than

To minimize delay cost of flights in multiple airports, this paper studied flights assignment problem under delay conditions. By considering the delay cost, airport capacity, and the slot exchange between airlines, this paper proposed a novel assignment model based on game theory and CDM mechanism. An improved ant colony algorithm was proposed to solve the flight assignment problem. The case studies showed that the proposed model can optimize the minimum delay cost between airlines under multiairport capacity constraints. The performance of proposed method was better than that of traditional non-slot-exchange method.

A Particle Swarm Optimizer Based Approach for Aircraft Parking Position Assignment

2015 ◽  
Vol 713-715 ◽  
pp. 1525-1529
Author(s):  
Di Ming Ai ◽  
Yu Fei Jia ◽  
Jun Yan Zhao ◽  
Ling Jie Kong
Keyword(s):  
Numerical Experiment ◽  
Assignment Problem ◽  
Optimization Problem ◽  
Particle Swarm ◽  
Optimization Strategy ◽  
Particle Swarm Optimizer ◽  
Assignment Model ◽  
Proposed Model ◽  
Complex Optimization

A aircraft parking position assignment problem is a complex optimization problem with many constrains. In this paper, an assignment model is built with the consideration of constrain treatment. A 2 neighborhood particle swarm optimizer is adopted. The numerical experiment results demonstrate the effectiveness of proposed model and optimization strategy.

scholarly journals Probabilistic Flight Delay Predictions Using Machine Learning and Applications to the Flight-to-Gate Assignment Problem

Aerospace ◽  
2021 ◽  
Vol 8 (6) ◽  
pp. 152
Author(s):  
Micha Zoutendijk ◽  
Mihaela Mitici
Keyword(s):  
Assignment Problem ◽  
Absolute Error ◽  
Aviation Industry ◽  
Probabilistic Forecasting ◽  
Flight Delays ◽  
Mixture Density ◽  
Assignment Model ◽  
Gate Assignment ◽  
Flight Delay ◽  
Delay Prediction

The problem of flight delay prediction is approached most often by predicting a delay class or value. However, the aviation industry can benefit greatly from probabilistic delay predictions on an individual flight basis, as these give insight into the uncertainty of the delay predictions. Therefore, in this study, two probabilistic forecasting algorithms, Mixture Density Networks and Random Forest regression, are applied to predict flight delays at a European airport. The algorithms estimate well the distribution of arrival and departure flight delays with a Mean Absolute Error of less than 15 min. To illustrate the utility of the estimated delay distributions, we integrate these probabilistic predictions into a probabilistic flight-to-gate assignment problem. The objective of this problem is to increase the robustness of flight-to-gate assignments. Considering probabilistic delay predictions, our proposed flight-to-gate assignment model reduces the number of conflicted aircraft by up to 74% when compared to a deterministic flight-to-gate assignment model. In general, the results illustrate the utility of considering probabilistic forecasting for robust airport operations’ optimization.

An Unequal-Sized Unidirectional Loop Layout Design Problem Considering Empty Vehicle Trip

2010 ◽  
Vol 37-38 ◽  
pp. 116-121
Author(s):  
Yu Lan Li ◽  
Bo Li ◽  
Su Jun Luo
Keyword(s):  
Material Handling ◽  
Design Principle ◽  
Facility Layout ◽  
Original Model ◽  
Layout Problem ◽  
Proposed Model ◽  
Loop Layout ◽  
Material Handling Costs ◽  
Loop Layout Problem ◽  
Better Than

In the facility layout decisions, the previous general design principle is to minimize material handling costs, and the objective of these old models only considers the costs of loaded trip, without regard to empty vehicle trip costs, which do not meet the actual demand. In this paper, the unequal-sized unidirectional loop layout problem is analyzed, and the model of facility layout is improved. The objective of the new model is to minimize the total loaded and empty vehicle trip costs. To solve this model, a heuristic algorithm based on partheno-genetic algorithms is designed. Finally, an unequal-sized unidirectional loop layout problem including 12 devices is simulated. Comparison shows that the result obtained using the proposed model is 20.4% better than that obtained using the original model.

Multi-Objective Fleet Assignment Problem Based on Self-Adaptive Genetic Algorithm

2013 ◽  
Vol 694-697 ◽  
pp. 2895-2900 ◽  
Author(s):  
Xiao Yang ◽  
Bo Jiang
Keyword(s):  
Genetic Algorithm ◽  
Carbon Emissions ◽  
Assignment Problem ◽  
Network Capacity ◽  
Total Carbon ◽  
Adaptive Genetic Algorithm ◽  
Multi Objective ◽  
Route Network ◽  
Assignment Model ◽  
Key Factor

Since the beginning of the twenty-first century, energy conservation has become the theme of the development of the world. China government set the emissions-reduction targets in various industries on the 12th Five-Year Plan. And the airlines were committed to reduce their carbon emissions. From an operational perspective, the airline model assignment problem is a key factor of the total carbon emissions on the entire route network. But the traditional aircraft assignment models approach did not account for this purpose to reduce carbon emissions. By constructing the multi-objective optimization models consider carbon emissions assignment model using a genetic algorithm, numerical example shows that the model is able to meet all aspects demand which include meeting route network capacity demand, minimizing operating costs and reducing total aircraft fleet carbon emissions.

scholarly journals The coalescent process in models with selection, recombination and geographic subdivision

1991 ◽  
Vol 57 (1) ◽  
pp. 83-91 ◽  
Author(s):  
Norman Kaplan ◽  
Richard R. Hudson ◽  
Masaru Iizuka
Keyword(s):  
Genetic Variation ◽  
Population Genetic ◽  
Genetic Model ◽  
Sequence Data ◽  
Balancing Selection ◽  
Similar Model ◽  
Proposed Model ◽  
Coalescent Approach ◽  
Neutral Mutations ◽  
Better Than

SummaryA population genetic model with a single locus at which balancing selection acts and many linked loci at which neutral mutations can occur is analysed using the coalescent approach. The model incorporates geographic subdivision with migration, as well as mutation, recombination, and genetic drift of neutral variation. It is found that geographic subdivision can affect genetic variation even with high rates of migration, providing that selection is strong enough to maintain different allele frequencies at the selected locus. Published sequence data from the alcohol dehydrogenase locus of Drosophila melanogaster are found to fit the proposed model slightly better than a similar model without subdivision.

scholarly journals Both Freud and Hoffman are Right: Anxious-Aggressive and Empathic Dimensions of Guilt

2008 ◽  
Vol 11 (1) ◽  
pp. 159-171 ◽  
Author(s):  
Itziar Etxebarria ◽  
Pedro Apodaca
Keyword(s):  
Young Adults ◽  
Subjective Experience ◽  
Negative Emotions ◽  
The Other ◽  
Point Scale ◽  
Nested Models ◽  
Proposed Model ◽  
Better Than

The purpose of the study was to confirm a model which proposed two basic dimensions in the subjective experience of guilt, one anxious-aggressive and the other empathic, as well as another dimension associated but not intrinsic to it, namely, the associated negative emotions dimension. Participants were 360 adolescents, young adults and adults of both sexes. They were asked to relate one of the situations that most frequently caused them to experience feelings of guilt and to specify its intensity and that of 9 other emotions that they may have experienced, to a greater or lesser extent, at the same time on a 7-point scale. The proposed model was shown to adequately fit the data and to be better than other alternative nested models. This result supports the views of both Freud and Hoffman regarding the nature of guilt, contradictory only at a first glance.

scholarly journals Order-Dependent Event Models for Agent Interactions

2020 ◽  
Author(s):  
Debarun Bhattacharjya ◽  
Tian Gao ◽  
Dharmashankar Subramanian
Keyword(s):  
Arrival Rate ◽  
Event Data ◽  
Political Event ◽  
Instantaneous Rate ◽  
Agent Interactions ◽  
Occurrence Data ◽  
Proposed Model ◽  
Event Models ◽  
Better Than ◽  
Event Occurrence

In multivariate event data, the instantaneous rate of an event's occurrence may be sensitive to the temporal sequence in which other influencing events have occurred in the history. For example, an agent’s actions are typically driven by preceding actions taken by the agent as well as those of other relevant agents in some order. We introduce a novel statistical/causal model for capturing such an order-sensitive historical dependence, where an event’s arrival rate is determined by the order in which its underlying causal events have occurred in the recent past. We propose an algorithm to discover these causal events and learn the most influential orders using time-stamped event occurrence data. We show that the proposed model fits various event datasets involving single as well as multiple agents better than baseline models. We also illustrate potentially useful insights from our proposed model for an analyst during the discovery process through analysis on a real-world political event dataset.

scholarly journals Improvements on Learning Kernel Extended Dictionary for Face Recognition

2020 ◽  
Vol 34 (4) ◽  
pp. 387-394
Author(s):  
Soodabeh Amanzadeh ◽  
Yahya Forghani ◽  
Javad Mahdavi Chabok
Keyword(s):  
Sparse Representation ◽  
Face Image ◽  
Collaborative Representation ◽  
Training Images ◽  
Input Face ◽  
Proposed Model ◽  
Eigen Values ◽  
New Type ◽  
The Mean ◽  
Better Than

Kernel extended dictionary learning model (KED) is a new type of Sparse Representation for Classification (SRC), which represents the input face image as a linear combination of dictionary set and extended dictionary set to determine the input face image class label. Extended dictionary is created based on the differences between the occluded images and non-occluded training images. There are four defaults to make about KED: (1) Similar weights are assigned to the principle components of occlusion variations in KED model, while the principle components of the occlusion variations have different weights, which are proportional to the principle components Eigen-values. (2) Reconstruction of an occluded image is not possible by combining only non-occluded images and the principle components (or the directions) of occlusion variations, but it requires the mean of occlusion variations. (3) The importance and capability of main dictionary and extended dictionary in reconstructing the input face image is not the same, necessarily. (4) KED Runtime is high. To address these problems or challenges, a novel mathematical model is proposed in this paper. In the proposed model, different weights are assigned to the principle components of occlusion variations; different weights are assigned to the main dictionary and extended dictionary; an occluded image is reconstructed by non-occluded images and the principle components of occlusion variations, and also the mean of occlusion variations; and collaborative representation is used instead of sparse representation to enhance the runtime. Experimental results on CAS-PEAL subsets showed that the runtime and accuracy of the proposed model is about 1% better than that of KED.

scholarly journals Voltage Balance Control Analysis of Three-Level Boost DC-DC Converters: Theoretical Analysis and DSP-Based Real Time Implementation

Energies ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 3073 ◽  
Author(s):  
Driss Oulad-Abbou ◽  
Said Doubabi ◽  
Ahmed Rachid
Keyword(s):  
Fuzzy Controller ◽  
Balance Control ◽  
Control Analysis ◽  
Signal Model ◽  
Small Perturbations ◽  
Proposed Model ◽  
Voltage Balance ◽  
Voltage Balance Control ◽  
Reduced Time ◽  
Better Than

In this paper, a step-by-step description to get a unique three-level boost DC–DC converter (TLBDC) (DC—direct current) small signal model is first presented and validated through simulations and experiments. This model allows for overcoming the usage of two sub-models as in the conventional modeling approach. Based on this model, voltage balance (VB) controllers are designed and VB control analysis is presented. Two VB controllers, namely Proportional Integral (PI) and Fuzzy, were analyzed when the VB control was applied on both TLBDC switches or only one. According to the obtained simulation and experimental results, the proposed model gives an accurate approximation in dynamic, small perturbations around an operating point and steady state modes. Moreover, it has been shown that VB is achieved in a reduced time when VB control is applied on both the TLBDC’s switches. Furthermore, the Fuzzy controller performs better than PI controller for VB control.

Sign in / Sign up

Export Citation Format

Share Document