Optimal Consumption Path Research Articles

Finding the optimal reliable energy consumption path for electric vehicles under rainfall conditions

ABSTRACT This paper presents a new path-finding problem to ensure reliable energy consumption for electric vehicles (EVs) under rainfall conditions. The objective function of the proposed model aims to find a reliable path that minimises energy consumption while ensuring a certain probability of completing the trip without exhausting a given battery energy budget. By considering the influence of adverse weather conditions at different periods, the existing model is expanded. To address the non-additivity and non-linearity characteristics of the optimisation model, an enhanced heuristic algorithm is proposed, incorporating inequality techniques, the K-shortest algorithm, and path-updating strategies. Lastly, the proposed algorithm is validated using Hong Kong’s grid-based road network as a case study, which demonstrates the correctness and effectiveness of the algorithm. The results indicate that by considering adverse weather conditions, the estimation of energy consumption can be significantly improved in terms of accuracy, achieving more efficient and reliable optimal path recommendations.

Hyperbolic discounting and state‐dependent commitment

AbstractIn a stochastic economy with uninsurable endowment risk, we establish a condition under which hyperbolic‐discounting consumers commit to a future consumption path using both illiquid assets and borrowing constraints as commitment devices. There is the possibility that a state‐dependent commitment can be adopted as an equilibrium consumption strategy. On a path leading to low future endowment, the current self can commit to its own optimal consumption path, which is undesirable for future selves. In contrast, along the path with a high future endowment, the current self cannot make a commitment and must accept a consumption allocation that future selves will revise. Thus, depending on what stochastic state will arise, people cannot fully utilize the available commitment devices in risky situations.

Optimal Energy Consumption Path Planning for Unmanned Aerial Vehicles Based on Improved Particle Swarm Optimization

In order to enhance the energy efficiency of unmanned aerial vehicles (UAVs) during flight operations in mountainous terrain, this research paper proposes an improved particle swarm optimization (PSO) algorithm-based optimal energy path planning method, which effectively reduces the non-essential energy consumption of UAV during the flight operations through a reasonable path planning method. First, this research designs a 3D path planning method based on the PSO optimization algorithm with the goal of achieving optimal energy consumption during UAV flight operations. Then, to overcome the limitations of the classical PSO algorithm, such as poor global search capability and susceptibility to local optimality, a parameter adaptive method based on deep deterministic policy gradient (DDPG) is introduced. This parameter adaptive method dynamically adjusts the main parameters of the PSO algorithm by monitoring the state of the particle swarm solution set. Finally, the improved PSO algorithm based on parameter adaptive improvement is applied to path planning in mountainous terrain environments, and an optimal energy-consuming path-planning algorithm for UAVs based on the improved PSO algorithm is proposed. Simulation results show that the path-planning algorithm proposed in this research effectively reduces non-essential energy consumption during UAV flight operations, especially in more complex terrain scenarios.

Changing the Discount Rate by Adjusting the Pure Rate of Time Preference

The Ramsey (1928) equation decomposes the real discount rate into the pure rate of time preference plus a term that accounts for the changing marginal utility of consumption. Discussions about the appropriate discount rate to apply in Cost Benefit Analysis sometimes refer to variations induced by alternative values of the pure rate of time preference as if the two vary on a one-to-one basis. But the optimal consumption path, which determines the marginal product of capital and hence the discount rate, depends on the rate of time preference. Hence the discount rate depends on time preference through the marginal utility term. We derive an analytical expression of this relationship and show that the derivative of the discount rate with respect to time preference only equals unity in the steady state and converges from below. We estimate the derivative using US data from 1930 to 2015. Based on a semi-parametric regression model with time-varying coefficients we find it is about 0.9, but we cannot rule out 1.0 being included in the 95% confidence interval. The implied pure rate of time preference after 1980 is about 1.6 percent.

Optimal Consumption Under a Habit-Formation Constraint: The Deterministic Case

We formulate and solve a deterministic optimal consumption problem to maximize the discounted constant relative risk aversion utility of an individual’s consumption-to-habit process assuming they only invest in a riskless market and that they are unwilling to consume at a rate below a certain proportion of their consumption habit. Increasing increases the degree of addictiveness of habit formation, with (respectively, ) corresponding to nonaddictive (respectively, completely addictive) model. We derive the optimal consumption policies explicitly in terms of the solution of a nonlinear free-boundary problem, which we analyze in detail. Impatient individuals (or, equivalently, those with more addictive habits) always consume above the minimum rate; thus, they eventually attain the minimum wealth-to-habit ratio. Patient individuals (or, equivalently, those with less addictive habits) consume at the minimum rate if their wealth-to-habit ratio is below a threshold and above it otherwise. By consuming patiently, these individuals maintain a wealth-to-habit ratio that is greater than the minimum acceptable level. Additionally, we prove that the optimal consumption path is hump-shaped if the initial wealth-to-habit ratio is either (1) larger than a high threshold or (2) below a low threshold and the agent is more risk seeking (that is, less risk averse). Thus, we provide a simple explanation for the consumption hump observed by various empirical studies.

Optimal Energy Consumption Path Planning for Quadrotor UAV Transmission Tower Inspection Based on Simulated Annealing Algorithm

In order to improve the efficiency of UAVs in transmission tower inspections, the UAV transmission tower inspection energy consumption model is proposed for the existing research in which there is no accurate energy consumption calculation method in transmission tower inspection, and the optimal energy consumption path for UAV transmission tower inspection is designed by combining with simulated annealing algorithm. Firstly, a real experimental environment is built for experimental data collection and analysis, and the energy consumption model for transmission tower inspection is constructed and the influencing factors are discussed and analyzed, and the energy consumption coefficients under different situations are obtained. Second, according to the constructed transmission tower inspection energy consumption model combined with the path planning algorithm, experimental simulation is conducted to plan the optimal energy consumption inspection path, and finally, the above results are verified by carrying out actual measurement experiments. The simulation results show that under different constant loads, the optimal energy consumption path in this paper can save 36.53% and 27.32% compared with the conventional path; compared with the shortest path, it can save 11.16% and 0.45%. The optimal energy consumption path of UAV transmission tower inspection based on the simulated annealing algorithm proposed in this paper effectively improves the efficiency of UAV transmission tower inspection.

Energy optimised D* AUV path planning with obstacle avoidance and ocean current environment

AbstractFor the path planning of autonomous underwater vehicles (AUVs) in the ocean environment, in addition to the planned path length and safe obstacle avoidance, it is also necessary to pay attention to the impact of ocean currents on the planned path. Therefore, this paper improves the original D* algorithm, and adds the obstacle cost item and the steering angle cost item as constraints on the basis of the original cost function, thus ensuring the navigation safety of the AUV. Considering that ocean currents have a greater impact on the energy consumption of AUVs, this paper establishes a cost model for the impact of ocean currents on AUV energy consumption and applies it to the D* path planning algorithm, so that AUVs can use ocean currents to reduce energy consumption, which can be seen through simulation experiments. The simulation results show that the improvement of the algorithm can plan an optimal energy consumption path.

A Novel Energy-Efficient, Static Scenario-Oriented Routing Method of Wireless Sensor Network Based on Edge Computing

In wireless sensor network (WSN), the energy of sensor nodes is limited. Designing efficient routing method for reducing energy consumption and extending the WSN’s lifetime is important. This paper proposes a novel energy-efficient, static scenario-oriented routing method of WSN based on edge computing named the NEER, in which WSN is divided into several areas according to the coverage of gateway (or base station), and each of the areas is regarded as an edge area network (EAN). Each edge area network is abstracted into a weighted undirected graph model combined with the residual energy of the sensor nodes. The base station (or a gateway) calculates the optimal energy consumption path for all sensor nodes within its coverage, and the nodes then perform data transmission through their suggested optimal paths. The proposed method is verified by the simulations, and the results show that the proposed method may consume about 37% less energy compared with the conventional WSN routing protocol and can also effectively extend the lifetime of WSN.

Optimal annuitisation in a deterministic financial environment

The global reforms to public pension schemes over the last thirty years have progressively reduced individuals’ post-retirement social security income. In order to compensate for this, individuals join pension funds and individual plans to increase their wealth at retirement. These types of fully funded plans generally give individuals the opportunity to withdraw the capital accumulated into their scheme or to convert it into an annuity. In this paper, we analyse individuals’ post-retirement choices to allocate the wealth at retirement between consumption, risk-free investments and a life annuity. We develop a discrete time optimisation model, in a deterministic framework, with a constant relative risk aversion (CRRA) utility function. We study the effect of a bequest motive and the annuity rate used by the insurer on the optimal choice. Several numerical applications are presented to illustrate the optimal annuitisation decision results and the optimal consumption paths.

Optimal Consumption Under a Habit-Formation Constraint

We propose a new optimal consumption model in which the degree of addictiveness of habit formation is directly controlled through a constraint on admissible consumption. In particular, we assume that the individual is unwilling to consume at a rate below a certain proportion 0<α≤1 of her consumption habit, which is the exponentially-weighted average of past consumption rates. α=1 prohibits the habit process to decrease and corresponds to the completely addictive model. α=0 makes the habit-formation constraint moot and corresponds to the non-addictive model. 0<α<1 leads to partially addictive models, with the level of addictiveness increasing with α. In contrast to the existing habit-formation literature, our constraint cannot be incorporated in the objective function through infinite marginal utility, and alters the analysis of the corresponding control problem. Assuming that the individual invests in a risk-free market, we formulate and solve an infinite-horizon, deterministic control problem to maximize the discounted CRRA utility of the individual's consumption-to-habit process subject to the said habit-formation constraint. We derive the optimal consumption policies explicitly in terms of the solution of a nonlinear free-boundary problem, which we analyze in detail. Impatient individuals (or, equivalently, those with more addictive habits) always consume above the minimum rate; thus, they eventually attain the minimum wealth-to-habit ratio. Patient individuals (or, equivalently, those with less addictive habits) consume at the minimum rate if their wealth-to-habit ratio is below a threshold, and above it otherwise. By consuming patiently, these individuals maintain a wealth-to-habit ratio that is greater than the minimum acceptable level. Additionally, we prove that the optimal consumption path is hump-shaped if the initial wealth-to-habit ratio is either: (1) larger than a high threshold; or (2) below a low threshold and the agent is more risk seeking (that is, less risk averse). Thus, we provide a simple explanation for the consumption hump observed by various empirical studies.

Do Natural Disasters Make Sustainable Growth Impossible?

We consider the prospects for sustainable growth using expected utility models of optimal investment under threat from natural disasters. Adoption of a continuous time, stochastic Ramsey growth model over an infinite time horizon permits the analysis of sustainability under uncertainty regarding adverse events, including both one-time and recurrent disasters. As appropriate to small economies, we consider adaptation to the risk of disaster. Natural disasters reduce capital stocks and disrupt the optimal consumption and felicity paths. While the time path of inter-temporal welfare might consequently shift downward, the path may still be non-decreasing over time, even without adding strong or weak sustainability constraints. Prudent disaster preparedness includes precautionary investment in productive capital, programs of adaptation to disaster risk, and avoiding distortionary policies undermining the prospects of optimality and sustainability.

Addiction to a Network

We characterize dynamic rational addiction to a harmful product by an informed individual who is connected to a network of users of the addictive product. The network harms the individual and imposes peer pressure on her to consume the addictive product. The network contributes to the state variable of accumulated stock affecting the individual. We identify the size of a network that causes the individual to start consuming the addictive product and become addicted. For an individual particularly prone to addiction, who may also abstain from the product, a network contributing to the individual's stock more than the individual's per-period income causes the individual's unique steady state to be that of maximum consumption of the addictive product. The network lowers the critical level above which the individual's optimal consumption path converges to a high steady state. An addicted individual always increases her steady state consumption due to any increase in the network, despite the harmful future repercussions of such increased consumption. “Rehabilitation” (redefined as disconnection from the network's peer pressure, reduction of the network's size, shortening the period of exposure to the network, or reducing the network's consumption) can prevent addiction if implemented early enough along the individual's optimal consumption path.

The invariant distribution of wealth and employment status in a small open economy with precautionary savings

We study optimal savings in continuous time with exogenous transitions between employment and unemployment as the only source of uncertainty in a small open economy. We prove the existence of an optimal consumption path. We exploit that the dynamics of consumption and wealth between jumps can be expressed as a Fuchsian system. We derive conditions under which an invariant joint distribution for the state variables , i.e., wealth and labour market status, exists and is unique. We also provide conditions under which the distribution of these variables converges to the invariant distribution. Our analysis relies on the notion of T-processes and applies results on the stability of Markovian processes from Meyn and Tweedie (1993a, b,c).

Optimal consumption decisions of family networks with similar felicity functions

Family networks have increased at an accelerated pace through social networking through social networking services, online platforms, and social media clubs. This paper develops a model of an economy populated by networks of families with similar preferences (the same functional form of the felicity or utility function) but family members differ in their deep parameters (compulsion for consumption and risk tolerance), which, in turn, leads to some kind o heterogeneity among the families. In this context, the problem of felicity (utility) maximization of the average family in the network is solved. The optimal path of consumption is obtained for the average family and graphical comparative static exercises are performed. Finally, the economic welfare of the typical family in a network is calculated and comparative static experiments are carried out. This approach improves the understanding of the consumption decision making of families interacting in social networking services.

Does microcredit increase household food consumption? A study of rural Vietnam

Although microcredit is considered a crucial tool for economic development, its contribution to improving the welfare of poor households is not well established. This study investigates this issue. We start with a theoretical model in which microcredit is used to finance the family business of a representative household. The household maximises its lifetime utility, which yields a dynamic optimal consumption path as a function of microcredit borrowing. Guided by the theoretical model, we then empirically estimate the impact of microcredit using a panel dataset of rural Vietnamese households for the period 2008–2016. We find that microcredit programs in rural Vietnam were effective in raising household food consumption in both the short and long terms. Nevertheless, the burden of loan repayment may have diminished food consumption with a lag.

Utility From Anticipation and Consumption Choices

This paper investigates the effects of anticipatory feelings on patience and the resulting intertemporal choices in finite horizon economy. Utility from anticipation of future consumption makes consumers patient. Furthermore, in general, it makes them more/less patient for near future choices than distant future choices, which causes time- inconsistency. To overcome time-inconsistency, sophisticated consumers adjust their discount factors. The resulting optimal consumption path may not be monotonic and it may exhibit hump-shaped or U-shaped. Furthermore, discount factors estimated from the optimal consumption path differ from true time preference and observational equivalence is no longer valid.

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An Artificial Bee Colony-Based Green Routing Mechanism in WBANs for Sensor-Based E-Healthcare Systems.

At present, sensor-based E-Healthcare systems are attracting more and more attention from academia and industry. E-Healthcare systems are usually a Wireless Body Area Network (WBANs), which can monitor or diagnose human health by placing miniaturized, low-power sensor nodes in or on patient’s bodies to measure various physiological parameters. However, in this process, WBAN nodes usually use batteries, and especially for implantable flexible nodes, it is difficult to accomplish the battery replacement, so the energy that the node can carry is very limited, making the efficient use of energy the most important problem to consider when designing WBAN routing algorithms. By considering factors such as residual energy of node, the importance level of nodes, path cost and path energy difference ratios, this paper gives a definition of Optimal Path of Energy Consumption (OPEC) in WBANs, and designs the Optimal Energy Consumption routing based on Artificial Bee Colony (ABC) for WBANs (OEABC). A performance simulation is carried out to verify the effectiveness of the OEABC. Simulation results demonstrate that compared with the genetic algorithm and ant colony algorithm, the proposed OEABC has a better energy efficiency and faster convergence rate.

Life Insurance and Annuity Demand under Hyperbolic Discounting

In this paper, we analyse and construct a lifetime utility maximisation model with hyperbolic discounting. Within the model, a number of assumptions are made: complete markets, actuarially fair life insurance/annuity is available, and investors have time-dependent preferences. Time dependent preferences are in contrast to the usual case of constant preferences (exponential discounting). We find: (1) investors (realistically) demand more life insurance after retirement (in contrast to the standard model, which showed strong demand for life annuities), and annuities are rarely purchased; (2) optimal consumption paths exhibit a humped shape (which is usually only found in incomplete markets under the assumptions of the standard model).

Annuitization of Retirement Assets and Optimal Consumption Paths

Annuitization of Retirement Assets and Optimal Consumption Paths