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.

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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

Value of travel time (VOTT) is a fundamental index in transportation economics, which represents the trip cost that the travelers are willing to pay for saving their travel time, working as a communicator between money and time. VOTT is of great importance in urban transportation planning and traffic forecasting as VOTT of travelers will impact on their traveling mode, frequency and routes. VOTT is calculated by estimating the ratio of the utility function on travel time and cost. The model is specified through logit regression analysis. In this paper, a stated preference survey on the VOTT of travelers is conducted in Nanjing, China. We adopt mixed logit model, which is a flexible model that allows the parameters to vary across the population and is not restricted by the IIA property, to perform the regression, and analyze the distribution of VOTT.

Estimating the Value of Travel Time Using Mixed Logit Model: A Practical Survey in Nanjing

Modelling for Joint Urban Parking Charge and Park-and-Ride Scheme in a Multimodal Transport Network

Malformed Intersection Level of Service Promotion Strategy Research Based on VISSIM

The near-threshold design is widely employed in the energy-efficient circuits, but it suffers from a high sensitivity to process variation, which leads to 2X delay variation due to temperature effects. Hence, it is not negligible. In this paper, we propose an analytical model for gate delay variation considering temperature effects in the near-threshold region. The delay variation model is constructed based on the log-skew-normal distribution by moment matching. Moreover, to deal with complex gates, a multi-variate threshold voltage approximation approach of stacked transistors is proposed. Also, three delay metrics (delay variability, ± 3 σ percentile points) are quantified and have a comparison with other known works. Experimental results show that the maximum of delay variability is 5% compared with Monte Carlo simulation and improves 5X in stacked gates compared with lognormal distribution. Additionally, it is worth mentioning that, the proposed model exhibits excellent advantages on − 3 σ and stacked gates, which improves 5X–10X in accuracy compared with other works.

https://www.mdpi.com/2079-9292/8/5/501/pdf

Zhiyuan Liu

Papers

Estimating the Value of Travel Time Using Mixed Logit Model: A Practical Survey in Nanjing

Modelling for Joint Urban Parking Charge and Park-and-Ride Scheme in a Multimodal Transport Network

Malformed Intersection Level of Service Promotion Strategy Research Based on VISSIM

Analytical Gate Delay Variation Model with Temperature Effects in Near-Threshold Region Based on Log-Skew-Normal Distribution

Large-scale intermodal liner shipping service network design