Sustainable Land Use and Water Management in Mountain Ecosystem - Case Study of a Watershed in the Indian Himalayas

The paper proposes to analyze the problem of choice of land use and technology for forest regeneration with minimum adverse impacts on the ecosystem. As the nature of the problem of such choice of land use and technology would depend upon the local characteristic of the ecosystem we propose to take up a case study through developing a model of analysis at the watershed level economies in the Himalayan mountains. The issue of choice, which is involved in the analysis of the particular case study, is supposed to yield valuable analytical and policy insights, which can be generalized for rural situations with similar geomorphic, eco-regional and agro-climatic conditions. This work develops a quantitative optimization framework of analysis using the mathematical tool of linear programming for structuring and articulating the problem of choice. The modeling framework essentially focuses on optimal use of land and energy resources in two alternate exercises of net revenue maximization and cost minimization. The range of options that the model would attempt to articulate through the case study would cover the following aspects: (a) Use of land for agriculture, pasture and forestry including conversion from one use to the other. (b) Choice of technology as determined by (i) seed (ii) water (iii) fertilizer (iv) animal energy and (vi) human labour. (c) Choices in commercial and non commercial fuel use for household and agriculture in the rural system taking account of the nexus between food and energy linked with the pattern of land use. The scope of analysis also covers the implication of choice in terms of the following impact on the global and local ecosystem. (a) Emissions in the form of carbon di oxide and methane from agricultural process and fuel use. (b) Soil erosion. While the model based case study work out the total water requirement for any land use pattern it has not considered any choice of source of water use, as there was no effective choice for the case study considered. The constraint of water availability has been taken into account to show how it drives the choice of technology and land use. A dynamic analysis of the problem would have been insightful however due to paucity of time series data on certain variables dynamic analysis wouldn’t be possible, instead the attempt here is to determine an alternate combination of inputs and land use pattern in an optimization exercise for a given year under different technologies. The attempt is to identify cost effective technologies, optimal land use pattern, input combinations and prescribe policies for adopting these technologies and help in attaining the optimal land use and input combinations for various outputs such that the impact on ecosystem is minimal.

The Voice of Optimization

We introduce the idea that using optimal classification trees (OCTs) and optimal classification trees with-hyperplanes (OCT-Hs), interpretable machine learning algorithms developed by Bertsimas and Dunn [2017, 2018], we are able to obtain insight on the strategy behind the optimal solution in continuous and mixed-integer convex optimization problem as a function of key parameters that affect the problem. In this way, optimization is not a black box anymore. Instead, we redefine optimization as a multiclass classification problem where the predictor gives insights on the logic behind the optimal solution. In other words, OCTs and OCT-Hs give optimization a voice. We show on several realistic examples that the accuracy behind our method is in the 90%-100% range, while even when the predictions are not correct, the degree of suboptimality or infeasibility is very low. We compare optimal strategy predictions of OCTs and OCT-Hs and feedforward neural networks (NNs) and conclude that the performance of OCT-Hs and NNs is comparable. OCTs are somewhat weaker but often competitive. Therefore, our approach provides a novel insightful understanding of optimal strategies to solve a broad class of continuous and mixed-integer optimization problems

Parametric shortest-path algorithms via tropical geometry

We study parameterized versions of classical algorithms for computing shortest-path trees. This is most easily expressed in terms of tropical geometry. Applications include shortest paths in traffic networks with variable link travel times.Comment: 24 pages and 8 figure

Optimizing Transportation Network of Recovering End-of-Life Vehicles by Compromising Program in Polymorphic Uncertain Environment

With rapid development of technology and improvement of living standards, the per capita holding of automobiles greatly increases, and the amount of end-of-life vehicles (ELVs) becomes larger and larger such that it is valuable to investigate an effective strategy for recycling ELVs from the viewpoints of environmental protection and resource utilization. In this paper, an optimization model with fuzzy and stochastic parameters is built to formulate the transportation planning problems of recycling ELVs in polymorphic uncertain environment, where the unit processing and transportation costs, the selling price of reused items, and the fixed cost are all fuzzy, while the demand in secondary market and the production capacity are random owing to features underlying the practical data. For this complicated polymorphic uncertain optimization model, a unified compromising approach is proposed to hedge the uncertainty of this model such that some powerful optimization algorithms can be applied to make an optimal recycling plan. Then, an interactive algorithm is developed to find a compromising solution of the uncertain model. Numerical results show efficiency of the algorithm and a number of important managerial insights are revealed from the proposed model by scenario analysis and sensitivity analysis. Document type: Articl

An analysis of short haul air passenger demand, volume 2

Several demand models for short haul air travel are proposed and calibrated on pooled data. The models are designed to predict demand and analyze some of the motivating phenomena behind demand generation. In particular, an attempt is made to include the effects of competing modes and of alternate destinations. The results support three conclusions: (1) the auto mode is the air mode's major competitor; (2) trip time is an overriding factor in intermodal competition, with air fare at its present level appearing unimportant to the typical short haul air traveler; and (3) distance appears to underly several demand generating phenomena, and therefore, must be considered very carefully to any intercity demand model. It may be the cause of the wide range of fare elasticities reported by researchers over the past 15 years. A behavioral demand model is proposed and calibrated. It combines the travel generating effects of income and population, the effects of modal split, the sensitivity of travel to price and time, and the effect of alternative destinations satisfying the trip purpose

The decision to migrate: A simultaneous decision making approach

Discrete choice models are used to investigate the individual’s choice among a discrete number of alternatives. The characteristics of each alternative, by means of multinomial and nested multinomial models, have been taken into account. Specifically, this study analyses the impact of choice-specific characteristics (economic and socio-political attributes) in a model of choice between different country locations. Individual IT-graduates are assumed to choose a single type of move, stay-home or go-abroad, while simultaneously choosing a country of their choice. We demonstrate that a nested logit model is appropriate on both theoretical and empirical grounds. The sample consists of 1,500 IT-graduates from India. The results show on the one hand a high migration propensity for foreign destinations and on the other hand a quite large number of IT-Graduates who want to stay at home. By comparing the direct elasticities (at branch level) of home with those of foreign destination types we observe that both the economic as well as socio-political factors tend to have a greater impact for the foreign destinations. Based on the cross elasticities values, a location comparison between the destinations Germany and the USA/Canada shows that the magnitude of the values of elasticities are found to be higher for North American countries than for Germany. This suggests that IT-Graduates evaluate the economic as well as the socio-political factors as more important and significantly higher for North American destinations than for Germany. In addition we find strong evidence for a competition between countries with high potentials, with India emerging as an attractive location. -- Mit Hilfe von Modellen für diskrete abhängige Variablen untersuchen wir die individuelle Auswahl aus einer Anzahl von Alternativen bei der Migration. Die Charakteristika der einzelnen Alternativen im Zusammenhang von Multinomialbzw. Nestedmodellen sind berücksichtigt worden. Wir untersuchen den Einfluss von auswahlspezifischen Charaktaristika (ökonomische u. sozio-politische) in einem Modell zur Auswahl zwischen verschiedenen Empfängerländern. ITHochschulabsolventen wählen ausgehend von zwei Alternativmöglichkeiten (Migration oder im Land bleiben), eine Alternative aus und wählen simultan ein bestimmtes Land. Es zeigt sich, dass ein „Nested-Logit-Modell“ sowohl in theoretischer als auch in empirischer Hinsicht für die Untersuchung am besten geeignet ist. Die Stichprobe besteht aus ca. 1500 IT-Hochschulabsolventen aus Indien. Die Ergebnisse zeigen einerseits eine höhere Neigung, ein ausländisches Land zu wählen, und andererseits tendiert eine große Anzahl von IT-Hochschulabsolventen, in der Heimat zu bleiben. Beim Vergleich der Direktelastizitäten für die erste Stufe beobachten wir für beide ökonomische und sozio-politische Faktoren einen höheren Einfluss auf die Entscheidung, ins Ausland zu gehen. Bei einem Standortvergleich zwischen Deutschland und dem klassischen Immigrationsland USA/Canada (basierend auf Kreuzelastizitäten) zeigt sich ferner, dass das Ausmaß der Elastizitätswerte höher für nordamerikanische Länder ist als für Deutschland. Dies bedeutet, dass die ITHochschulabsolventen die ökonomischen und sozio-politischen Faktoren für die nordamerikanischen Länder signifikant höher bewerten als für Deutschland. Zusätzlich finden wir Evidenz für die Existenz von starkem Wettbewerb zwischen Ländern um die IT-Hochschulabsolventen aus Indien, das selbst als ein attraktiver Standort gilt.

Three-D multilateration: A precision geodetic measurement system

A technique of satellite geodesy for determining the relative three dimensional coordinates of ground stations within one centimeter over baselines of 20 to 10,000 kilometers is discussed. The system is referred to as 3-D Multilateration and has applications in earthquake hazard assessment, precision surveying, plate tectonics, and orbital mechanics. The accuracy is obtained by using pulsed lasers to obtain simultaneous slant ranges between several ground stations and a moving retroreflector with known trajectory for aiming the lasers

A panel analysis of UK industrial company failure

We examine the failure determinants for large quoted UK industrials using a panel data set comprising 539 firms observed over the period 1988-93. The empirical design employs data from company accounts and is based on Chamberlain’s conditional binomial logit model, which allows for unobservable, firm-specific, time-invariant factors associated with failure risk. We find a noticeable degree of heterogeneity across the sample companies. Our panel results show that, after controlling for unobservables, lower liquidity measured by the quick assets ratio, slower turnover proxied by the ratio of debtors turnover, and profitability were linked to the higher risk of insolvency in the analysis period. The findings appear to support the proposition that the current cash-flow considerations, rather than the future prospects of the firm, determined company failures over the 1990s recession