Sustainable Economic Development: The Main Principles and the Basic Equation

This work offers system and information content of the following economic categories: development, sustainable economic development. The author has formulated the fundamental principles of sustainable development: the principle of minimum resource dissipation and the equation of self-organization, the law of conserving the economic potential of a social system. The basic equation of development has been formulated. The model of sustainable development is viewed on the basis of the equation.economic system sustainable development; economic system selforganization,model sustainable development of the economic system

Evaluating Projects and Assessing Sustainable Development in Imperfect Economies

We are interested in three related questions: (1) How should accounting prices be estimated? (2) How should we evaluate policy change in an imperfect economy? (3) How can we check whether intergenerational well-being will be sustained along a projected economic programme? We do not presume that the economy is convex, nor do we assume that the government optimizes on behalf of its citizens. We show that the same set of accounting prices should be used both for policy evaluation and for assessing whether or not intergenerational welfare along a given economic path will be sustained. We also show that a comprehensive measure of wealth, computed in terms of the accounting prices, can be used as an index for problems (2) and (3) above. The remainder of the paper is concerned with rules for estimating the accounting prices of several specific environmental natural resources, transacted in a few well known economic institutions.Sustainable development, Imperfect economies

A Stochastic Resource-Sharing Network for Electric Vehicle Charging

We consider a distribution grid used to charge electric vehicles such that voltage drops stay bounded. We model this as a class of resource-sharing networks, known as bandwidth-sharing networks in the communication network literature. We focus on resource-sharing networks that are driven by a class of greedy control rules that can be implemented in a decentralized fashion. For a large number of such control rules, we can characterize the performance of the system by a fluid approximation. This leads to a set of dynamic equations that take into account the stochastic behavior of EVs. We show that the invariant point of these equations is unique and can be computed by solving a specific ACOPF problem, which admits an exact convex relaxation. We illustrate our findings with a case study using the SCE 47-bus network and several special cases that allow for explicit computations.Comment: 13 pages, 8 figure

Effects of Time Horizons on Influence Maximization in the Voter Dynamics

In this paper we analyze influence maximization in the voter model with an active strategic and a passive influencing party in non-stationary settings. We thus explore the dependence of optimal influence allocation on the time horizons of the strategic influencer. We find that on undirected heterogeneous networks, for short time horizons, influence is maximized when targeting low-degree nodes, while for long time horizons influence maximization is achieved when controlling hub nodes. Furthermore, we show that for short and intermediate time scales influence maximization can exploit knowledge of (transient) opinion configurations. More in detail, we find two rules. First, nodes with states differing from the strategic influencer's goal should be targeted. Second, if only few nodes are initially aligned with the strategic influencer, nodes subject to opposing influence should be avoided, but when many nodes are aligned, an optimal influencer should shadow opposing influence.Comment: 22 page

Optimal Resource Allocation Over Time and Degree Classes for Maximizing Information Dissemination in Social Networks

We study the optimal control problem of allocating campaigning resources over the campaign duration and degree classes in a social network. Information diffusion is modeled as a Susceptible-Infected epidemic and direct recruitment of susceptible nodes to the infected (informed) class is used as a strategy to accelerate the spread of information. We formulate an optimal control problem for optimizing a net reward function, a linear combination of the reward due to information spread and cost due to application of controls. The time varying resource allocation and seeds for the epidemic are jointly optimized. A problem variation includes a fixed budget constraint. We prove the existence of a solution for the optimal control problem, provide conditions for uniqueness of the solution, and prove some structural results for the controls (e.g. controls are non-increasing functions of time). The solution technique uses Pontryagin's Maximum Principle and the forward-backward sweep algorithm (and its modifications) for numerical computations. Our formulations lead to large optimality systems with up to about 200 differential equations and allow us to study the effect of network topology (Erdos-Renyi/scale-free) on the controls. Results reveal that the allocation of campaigning resources to various degree classes depends not only on the network topology but also on system parameters such as cost/abundance of resources. The optimal strategies lead to significant gains over heuristic strategies for various model parameters. Our modeling approach assumes uncorrelated network, however, we find the approach useful for real networks as well. This work is useful in product advertising, political and crowdfunding campaigns in social networks.Comment: 14 + 4 pages, 11 figures. Author's version of the article accepted for publication in IEEE/ACM Transactions on Networking. This version includes 4 pages of supplementary material containing proofs of theorems present in the article. Published version can be accessed at http://dx.doi.org/10.1109/TNET.2015.251254

Green water re-capitalization for optimizing agricultural productivity in Eastern and Southern Africa

Irrigated farmingWater policy

On controllability of neuronal networks with constraints on the average of control gains

Control gains play an important role in the control of a natural or a technical system since they reflect how much resource is required to optimize a certain control objective. This paper is concerned with the controllability of neuronal networks with constraints on the average value of the control gains injected in driver nodes, which are in accordance with engineering and biological backgrounds. In order to deal with the constraints on control gains, the controllability problem is transformed into a constrained optimization problem (COP). The introduction of the constraints on the control gains unavoidably leads to substantial difficulty in finding feasible as well as refining solutions. As such, a modified dynamic hybrid framework (MDyHF) is developed to solve this COP, based on an adaptive differential evolution and the concept of Pareto dominance. By comparing with statistical methods and several recently reported constrained optimization evolutionary algorithms (COEAs), we show that our proposed MDyHF is competitive and promising in studying the controllability of neuronal networks. Based on the MDyHF, we proceed to show the controlling regions under different levels of constraints. It is revealed that we should allocate the control gains economically when strong constraints are considered. In addition, it is found that as the constraints become more restrictive, the driver nodes are more likely to be selected from the nodes with a large degree. The results and methods presented in this paper will provide useful insights into developing new techniques to control a realistic complex network efficiently

Research and Regions. a KWIC Indexed Bibliography

Computerized techniques applied to economics to produce bibliography of related materia

Entrepreneurial Ventures and the Developmental State: Lessons from the Advanced Economies

A basic intellectual challenge for those concerned with the poverty of nations is to come to grips with the nature and causes of the wealth of the world?s wealthier nations. One might then be in a position to inform the poorer nations how they might achieve similar outcomes. This paper is organized around what I call ?the theory of innovative enterprise?, a perspective derived from the historical and comparative study of the development of the advanced economies. The theory of innovative enterprise provides the essential analytical link between entrepreneurship and development. Section 2 offers, as a point of departure, a contrast between entrepreneurship in rich and poor nations. Section 3 outlines the theory of the innovating firm in which entrepreneurship has a role to play. Section 4 identifies the roles of entrepreneurship in new firm formation in terms of the types of strategy, organization, and finance that innovation requires, and emphasizes the ?disappearance? of entrepreneurship with the growth of the firm. In Section 5 I argue that, in the advanced economies, successful entrepreneurship in knowledge intensive industries has depended heavily upon a combination of business allocation of resources to innovative investment strategies, and government investment in the knowledge base, state sponsored protection of markets and intellectual property rights, and state subsidies to support these business strategies. One cannot understand national economic development without understanding the role of the developmental state. At the same time, the specific agenda and ultimate success of the developmental state cannot be understood in abstraction from the dynamics of innovative enterprise. It is through the interaction of the innovative enterprise and the developmental state that entrepreneurial activity inserts itself into the economic system to contribute to the process of economic development.entrepreneurship, innovative enterprise, developmental state