Time Variant Interval Linear Programming for Environmental Management Systems

Optimization technology is widely applied to maximize economic profit under ecology constrains in environmental management systems. To tackle the inherent uncertainties, inexact optimization methods have been proposed. Interval linear program- ming (ILP) model has drawn increasing scholarly attention. ILP describe uncertainty by one coarse scaled stochastic process. However, often involves multiple processes when zooming into high resolution. may not satisfied fine scale constraints. A time variant interval programming (TVILP) developed implement temporal downscaling, and likewise, a heuristic algorithm integrating dynamic proposed for Markov chained TVILP. Dynamic can converts complexity exponential polynomial. In current paper, performance of TVILP analyzed based on following three metrics: maximal (M_profit), constraint violation risk (CVR), path (MPR). The perfor- mance further compared with Best Worst method, classic model, contractor, Interval-parameter multi-stage programming. Experimental results reveal that provides refined solutions smaller granularity whose decision space contracts most possible transition paths. Unable obtain maxi- mum profit, though, does pose decreased risk, facilitating more feasible reliable decision-making management.