Network Equilibrium Analysis Research Articles

Impact of Interest Rate Risk on Supply Chain Network under Bank Credit and Trade Credit Financing

The purpose of this study is to propose a methodology that reflects the impact of interest rate risk on firms in supply chain network under bank financing and trade credit and further describe how trade credit improves the impact of interest rate risk on supply chain network through a financial flow equilibrium. A mean-variance framework and a network equilibrium analysis are integrated to provide a modeling framework. The model allows for the investigation of how bank credit financing (BCF) and trade credit financing (TCF) affect the payment strategy and financial flow of interconnected firms in supply chain networks and how they are affected by interest rate risks. The optimal behavior of manufacturers and retailers is described through variational inequality. We construct a supply chain network equilibrium model and derive qualitative properties of the solution and the function that becomes assimilated to the variational inequality problem. Additionally, variational inequality is solved using the modified projection method. This study extends the research on the impact of interest rate risk on the decision in supply chain network of firms. While other studies focus on the game between banks and firms, only a few authors have made attempts to examine the game between one manufacturer and one retailer in supply chain. An effective trade credit strategy is obtained by balancing cash and credit transactions. Through the case study, we learn how to balance the capital flow effectively to improve the negative impact of interest rate risk on supply chain.

Degradable transportation network with the addition of electric vehicles: Network equilibrium analysis.

Introducing electric vehicles (EVs) into urban transportation network brings higher requirement on travel time reliability and charging reliability. Specifically, it is believed that travel time reliability is a key factor influencing travelers’ route choice. Meanwhile, due to the limited cruising range, EV drivers need to better learn about the required energy for the whole trip to make decisions about whether charging or not and where to charge (i.e., charging reliability). Since EV energy consumption is highly related to travel speed, network uncertainty affects travel time and charging demand estimation significantly. Considering the network uncertainty resulted from link degradation, which influences the distribution of travel demand on transportation network and the energy demand on power network, this paper aims to develop a reliability-based network equilibrium framework for accommodating degradable road conditions with the addition of EVs. First, based on the link travel time distribution, the mean and variance of route travel time and monetary expenses related to energy consumption are deduced, respectively. And the charging time distribution of EVs with charging demand is also estimated. Then, a nested structure is considered to deal with the difference of route choice behavior derived by the different uncertainty degrees between the routes with and without degradable links. Given the expected generalized travel cost and a psychological safety margin, a traffic assignment model with the addition of EVs is formulated. Subsequently, a heuristic solution algorithm is developed to solve the proposed model. Finally, the effects of travelers’ risk attitude, network degradation degree, and EV penetration rate on network performance are illustrated through an example network. The numerical results show that the difference of travelers’ risk attitudes does have impact on the route choice, and the widespread adoption of EVs can cut down the total system travel cost effectively when the transportation network is more reliable.

Activity-based trip chaining behavior analysis in the network under the parking fee scheme

In this paper, we incorporate activity-based trip chaining behavior into the network equilibrium analysis. An integrated model which combines Beckman-type congestion link terms and entropy-type logit demand terms is proposed to describe the traveler behavior. The convexity and equivalency conditions of the model are discussed. Based on the integrated model, a bi-level model is designed to maximize the social welfare by appropriate parking fee. Also, an expanded network is developed to eliminate the non-additivity of the utilities of activities and travelling in the original network. Then, the Simulated Annealing (SA) method is used to solve the proposed bi-level model. Numerical examples are presented to examine the model’s availability and effects of the parking fee scheme on traveler behavior and social welfare. Results show that the model is effective in describing the trip chaining behavior in the network.

C-logit stochastic user equilibrium model with elastic demand

Modeling the elasticity of travel demand in network equilibrium analysis has several important transportation applications. In this paper, we provide a mathematical programming formulation for the C-logit stochastic user equilibrium problem with elastic demand (CL-SUE-ED) in the route domain. The proposed model is capable of explicitly modeling the elasticity of travel demand and the effect of route overlapping on travel choice and route choice simultaneously. Some qualitative properties of the model, including the equivalency and uniqueness of the solution, are also rigorously proved. To solve the CL-SUE-ED model, a partial linearization method is developed to handle the elastic demand and route overlapping considerations. In addition, a self-regulated averaging stepsize scheme is adopted to smartly determine the stepsize while avoiding evaluating the complex objective function. Numerical examples are also provided to demonstrate the features of the proposed model and solution algorithm.

Q-Generalized Logit Route Choice an Network Equilibrium Model

The multinomial logit model is expressed as a closed-form equation, and plays an important role in the field of tra sportation. The Gumbel-distributed utility in the multinomial logit model is restrictive in certain applications, especially in ro te choice behavior and network equilibrium analysis, although it is mathematically convenient. The range of variation of utility in the logit model is unbounded. The Gumbel distribution is left-skewed and has a very thi tail to the left. In additionFor example, the utility in the multinomial logit has a the homogeneity of homosce astic variance. In this study, the multinomial logit model is extended by generalizing the Gumbel-distributed utility to allow heteroscedastic variance and flexible shape. Then, the generalized logit model with a generalized Gumbel distribution is incorporated into the transportation network equilibrium model. The network equilibrium model with a generalized logit route choice is formulated as an optimization problem under uncongested networks. The objective function includes Tsallis entropy, which is a type of generalized entropy. In this study, the generalization of the Gumbel distribution, logit model, and network equilibrium model has a unified framework with q-analysis or Tsallis statistics.

A network equilibrium analysis on destination, route and parking choices with mixed gasoline and electric vehicular flows

In many countries across the world, fossil fuels, especially petroleum, are the largest energy source for powering the socio-economic system, and the transportation sector dominates the consumption of petroleum in these societies. As the petroleum price continuously climbs and the threat of global climate changes becomes more evident, the world is now facing critical challenges in reducing petroleum consumption and exploiting alternative energy sources. A massive adoption of plug-in electric vehicles (PEVs), especially battery electric vehicles (BEVs), offers a very promising approach to changing the current energy consumption structure and diminishing greenhouse gas emissions and other pollutants. Understanding how individual electric vehicle drivers behave subject to the technological restrictions and infrastructure availability and estimating the resulting aggregate supply–demand effects on urban transportation systems is not only critical to transportation infrastructure development, but also has determinant implications in environmental and energy policy enactment. This paper presents an equilibrium-based analytical tool for quantifying travel choice patterns in urban transportation networks with both gasoline and electric vehicular flows. Specifically, a network equilibrium problem with combined destination, route and parking choices subject to the driving range limit and alternative travel cost composition associated with BEVs are formulated, solved, and numerically analyzed under different network settings and scenarios. The defined problem introduces a new dimension of modeling network equilibrium problems with side constraints. The practical significance of the developed tool lies in its solution tractability and extension capability and its ease of being embedded into the existing urban travel demand forecasting framework.

A network analysis of developing brain cultures

We recorded electrical activity from four developing embryonic brain cultures (4–40 days in vitro) using multielectrode arrays (MEAs) with 60 embedded electrodes. Data were filtered for local field potentials (LFPs) and downsampled to 1 ms to yield a matrix of time series consisting of 60 electrode × 60 000 time samples per electrode per day per MEA. Each electrode time series was rendered stationary and nonautocorrelated by applying an ARIMA (25, 1, 1) model and taking the residuals (i.e. innovations). Two kinds of analyses were then performed. First, a pairwise crosscorrelation (CC) analysis (±25 1 ms lags) revealed systematic changes in CC with lag, day in vitro (DIV), and inter-electrode distance. Specifically, (i) positive CCs were 1.76× more prevalent and 1.44× stronger (absolute value) than negative ones, and (ii) the strength of CC increased with DIV and decreased with lag and inter-electrode distance. Second, a network equilibrium analysis was based on the instantaneous (1 ms resolution) logratio of the number of electrodes that were above or below their mean, called simultaneous departure from equilibrium, SDE. This measure possesses a major computational advantage over the pairwise crosscorrelation approach because it is very simple and fast to calculate, an important factor for the analysis of large networks. The results obtained with SDE covaried highly with CC over DIV, which further validates the usefulness of this measure as a computationally effective tool for large scale network analysis.

Assessment for Advanced Traveler Information Systems by Network Equilibrium Analysis

This study proposed the introductory effect of advanced traveler information systems using two methods, WTP and [MSUE/ATIS] model. First, we performed the citizen perception survey to the introductory effect of VICS-unit. We evaluated the value of MIS by WTP survey, and estimated the benefit Furthermore, the unknown parameter of [MSUE/ATIS] model was estimated using WTP model. Finally, [MSUE/ATIS] model was applied to Kumamoto Urban Area and Seien Urban Area in order to estimate the benefit. We found that the introductory of MIS in the area, where traffic congestion is heavy and travel cost is large, is effective.

Optimal Link Tolls under Nested Logit Type Stochastic User Equilibrium

There are some attempts to integrate congestion charging theory and transportation network equilibrium analysis but existing analyses are still far from reality such as using independent demand function. In this paper we analyze the optimal link tolls in the multi-modal network where users' behavior follows Nested Logit models based on random utility maximization theory. It will be shown that even in this situation the conventional marginal cost pricing is still one of the optimal tolls if objective function is social surplus that is consistent with users' behavioral model. We apply this model to Tokyo Metropolitan Area and compute optimal tolls in that large-scaled network.

General network equilibrium analysis

Network equilibrium problems, such as electric, hydraulic, traffic and economic equilibrium problems, are very common topics in real world situations. Equilibrium solutions can be characterized by various flow laws which govern the feasible flows on the underlying network, the dependent index quantity which is resulted by feasible flows, and the equilibrium principles which put the network system in a stable state. In this paper, a generalized complementary model is established for the general network equilibrium problems. Due to the nature of conical duality and complementary characterization of equilibrium solutions, under some monotonicity assumptions, the equilibrium problem is equivalent to the extremality conditions of a generalized geometric programming problem. Hence geometric programming methods can be applied to the network equilibrium analysis. Furthermore, the recent studies of Fang and Peterson (1982) in generalized variational inequalities can be adopted to handle more complicated cases. In ...

State of the Art—Networks of Queues: A Survey of Weak Convergence Results

This report is a sequel to our review paper, Lemoine [Lemoine, A. J. 1977. Networks of queues–A survey of equilibrium analysis. Management sci. 24 464–481.], on the equilibrium analysis of networks of queues. In this paper we review some weak convergence results for networks of queues, which include heavy traffic limit theorems for open networks and asymptotic results for large closed Markovian systems which are generalizations of the classical repairman problem. These weak convergence results justify certain approximation schemes for processes of interest. We also discuss some important open problems in the area of weak convergence results for networks of queues.