Software tools for stochastic programming: A Stochastic Programming Integrated Environment (SPInE)

SP models combine the paradigm of dynamic linear programming with modelling of random parameters, providing optimal decisions which hedge against future uncertainties. Advances in hardware as well as software techniques and solution methods have made SP a viable optimisation tool. We identify a growing need for modelling systems which support the creation and investigation of SP problems. Our SPInE system integrates a number of components which include a flexible modelling tool (based on stochastic extensions of the algebraic modelling languages AMPL and MPL), stochastic solvers, as well as special purpose scenario generators and database tools. We introduce an asset/liability management model and illustrate how SPInE can be used to create and process this model as a multistage SP application

Impacts of Reallocation of Resource Constraints on the Northeast Economy of Brazil

The present paper explores the role of water and energy resource constraints and allocation on the Northeast Brazil economy. The analysis centered on the creation of an intergrated model in which an econometric-input-output model was linked with a linear programming optimization model for resource allocation. Over the period 1999-2012, the impact on the six agricultural sectors was to reduce their output and employment by 15% annually. The reduction in employment in the rest of the economy was a little over 1% annually. However, since the agricultural sectors continue to employ a significant percentage of the labor force, the aggregate loss of employment amounted to 6% of the total regional employment on average, translating into 1 million jobs annually. When water allocation and energy resource allocations are considered simultaneously, the re-allocations are more limited, resulting in a loss of 0.78 million jobs annually. These results suggest the need for an active link between policy making and economic development when resource constraints are present. Some balance has to be provided between allocation and reallocation on the one hand perhaps driven by concerns with economic efficiency against anticipated losses of employment for part of the labor force with few other alternatives.

An asset and liability management (ALM) model using integrated chance constraints

This paper discusses and develops a Two Stage Integrated Chance Constraints Programming for the Employees Provident Fund Malaysia. The main aim is to manage, that is, balance assets and liabilities. Integrated Chance Constraints not only limit the event of underfunding but also the amount of underfunding. This paper includes the numerical illustration

CHANCE CONSTRAINED PROGRAMMING MODELS FOR RISK-BASED ECONOMIC AND POLICY ANALYSIS OF SOIL CONSERVATION

The random nature of soil loss under alternative land-use practices should be an important consideration of soil conservation planning and analysis under risk. Chance constrained programming models can provide information on the trade-offs among pre-determined tolerance levels of soil loss, probability levels of satisfying the tolerance levels, and economic profits or losses resulting from soil conservation to soil conservation policy makers. When using chance constrained programming models, the distribution of factors being constrained must be evaluated. If random variables follow a log-normal distribution, the normality assumption, which is generally used in the chance constrained programming models, can bias the results.Risk and Uncertainty,