In this paper, the analysis of recent advances in genetic algorithms is discussed. The genetic algorithms of great interest in research community are selected for analysis. This review will help the new and demanding researchers to provide the wider vision of genetic algorithms. The well-known algorithms and their implementation are presented with their pros and cons. The genetic operators and their usages are discussed with the aim of facilitating new researchers. The different research domains involved in genetic algorithms are covered. The future research directions in the area of genetic operators, fitness function and hybrid algorithms are discussed. This structured review will be helpful for research and graduate teaching.

/pdf/a-review-on-genetic-algorithm-past-present-and-future-2o5y8ru178.pdf

A review on genetic algorithm: past, present, and future

Investors systematically deviate from rationality when making financial decisions, yet the mechanisms responsible for these deviations have not been identified. Using event-related fMRI, we examined whether anticipatory neural activity would predict optimal and suboptimal choices in a financial decision-making task. We characterized two types of deviations from the optimal investment strategy of a rational risk- neutral agent as risk-seeking mistakes and risk-aversion mistakes. Nucleus accumbens activation preceded risky choices as well as risk- seeking mistakes, while anterior insula activation preceded riskless choices as well as risk-aversion mistakes. These findings suggest that distinct neural circuits linked to anticipatory affect promote different types of financial choices, and indicate that excessive activation of these circuits may lead to investing mistakes. Thus, consideration of anticipatory neural mechanisms may add predictive power to the rational actor model of economic decision-making.

The Neural Basis of Financial Risk Taking

Transportation research. part c, emerging technologies

Transportation Networks. Optimality. Cost Functions. Deterministic User Equilibrium Assignment. Stochastic User Equilibrium Assignment. Trip Table Estimation. Network Reliability. Network Design. Conclusions. References. Index.

Transportation network analysis

The efficiency of a transport system depends on several elements, such as available technology, governmental policies, the planning process, and control strategies. Indeed, the interaction between these elements is quite complex, leading to intractable decision making problems. The planning process and real-time control strategies have been widely studied in recent years, and there are several practical implementations with promising results. In this paper, we review the literature on Transit Network Planning problems and real-time control strategies suitable to bus transport systems. Our goal is to present a comprehensive review, emphasizing recent studies as well as works not addressed in previous reviews.

Planning, operation, and control of bus transport systems: A literature review

Examining the effects of the built environment on topological properties of the bike-sharing network in Suzhou, China

In recent years, the convolutional and recurrent neural networks are widely applied in traffic prediction tasks. Traffic speed prediction is an important and challenging topic in intelligent transportation systems. In this case, this paper proposes a hybrid deep learning structure for short-term traffic speed prediction, which combines convolutional neural networks and long short-term memory neural networks together. External factors such as weather condition and air quality can also affect the driving behavior of travelers and cause fluctuation of traffic speed. Based on theories in traffic engineering, we propose a data-fusion method to measure the impact of environmental factors. To enhance the performance of our model, we introduced attention mechanism to our model. With convolutional block attention module, our network could emphasize important channels and pixels of input features and suppress unnecessary ones. Comparing with several deep learning methods and hybrid deep learning structures, an experiment in one region of Suzhou which contains 909 links shows the outperformance of our model. Under different time steps, the prediction error of our model is lower than any other methods in urban expressway, primary-arterial, secondary-arterial, and branch-road. The results indicate that the spatial dependencies, the temporal correlations, and environmental impact should not be ignored in traffic speed prediction tasks.

/pdf/short-term-traffic-speed-prediction-of-urban-road-with-multi-gs4rgel61o.pdf

Short-Term Traffic Speed Prediction of Urban Road With Multi-Source Data

The follow up time is an important parameter for estimating the entry capacity of roundabouts. However, its variability and contributing factors have long been ignored in the literatures. In this study, 171 follow up samples and contributing factors (traffic volume, vehicle position, waiting vehicles behind, vehicle type, and drivers’ gender) are collected at a roundabout in Pacific Pines, Australia. It is found that the follow up time is indeed significantly affected by traffic volume, waiting vehicles behind, vehicle type, and drivers’ gender. In order to establish the relationship between the follow up time and its contributing factors, an inverse Gaussian regression model is further developed. This relationship could be applied to estimate the entry capacities by taking into account the variability of follow up samples. According to the model, the traffic volume and vehicle types are the most important contributing factors.

/pdf/modelling-follow-up-time-at-a-single-lane-roundabout-2g1f7cjhk6.pdf

Modelling follow up time at a single-lane roundabout

In this study, we propose a general stochastic ridesharing user equilibrium (SRUE) problem with elastic demand (ED) for urban transportation network analysis with ridesharing activities by extending the deterministic ridesharing user equilibrium (DRUE) problem, which is referred to as the general SRUE-ED problem. We develop a novel variational inequality (VI) model in terms of the Lagrange multipliers corresponding to the ride-matching constraints for the general SRUE-ED problem. The existence and uniqueness of the SRUE-ED solution are demonstrated under mild conditions. We proceed to put up a global convergent method to solve the developed VI model by incorporating the weighted cost averaging (WCA) method. The purpose of WCA method is to solve a parametric fixed-point model formulated for the general SRUE-ED problem without the ride-matching constraints. Finally, we use three numerical examples to provide practical insights into the operation and management of the ridesharing systems and to examine the effectiveness of the proposed model and solution method. 

General stochastic ridesharing user equilibrium problem with elastic demand

This study aimed to establish whether optimal stop spacing should vary by land use type. A new stop clustering method was proposed with stops divided into catchments on the basis of land use. A bilevel optimization model was then used to suggest optimal stop spacing for these catchments. The upper-level problem minimized a cost function that represented the perspectives of the passengers, the operators, and the local authority, and the lower-level problem was the transit assignment problem. Results show that stop spacing in the catchments with residential usage is generally larger than in those catchments with nonresidential or mixed land use. Near-optimal solutions were proposed to accommodate local considerations of stop placement. The spacing interval created by near-optimal solutions could be used to adjust existing stop placement. A case study of Tram Route 109 in Melbourne, Australia, revealed that the practical implication of the proposed analytical approach indeed improved the practical operations of the tram service. In future studies, the model could be extended to a network of tram routes. Overall, the results suggest that optimal stop spacing on public transport should be a function of land use type.

Zhiyuan Liu

Papers

Examining the effects of the built environment on topological properties of the bike-sharing network in Suzhou, China

Short-Term Traffic Speed Prediction of Urban Road With Multi-Source Data

Modelling follow up time at a single-lane roundabout

General stochastic ridesharing user equilibrium problem with elastic demand

Should Optimal Stop Spacing Vary by Land Use Type? - A New Methodology