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首页> 外文期刊>Journal of Hydroinformatics >Stochastic order-based optimal design of a surface reservoir-irrigation district system
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Stochastic order-based optimal design of a surface reservoir-irrigation district system

机译：基于随机顺序的地表水库灌区系统优化设计

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摘要

This paper explores the effects of streamf low uncertainty and the type of stochastic order, which is used for comparing stochastic variables, on optimal design of a reservoir multi-crop irrigation district system. Four nonlinear mathematical programs with an economic objective function including deterministic, stochastic-EXP with expected value order, stochastic-SD with stochastic dominance (SD) order, and stochastic-EGCL with expected gain-confidence limit (EGCL) order were developed. Afterwards, the approaches of successive linear programming (SLP) and PSO-MC, which combines particle swarm optimization (PSO) algorithm and Monte Carlo simulation (MC), to solve the programs were selected. Hajiarab Irrigation District located in Ghazvin Province of Iran was used as a case study and the results obtained from using different programs and solution approaches were analyzed and compared. Among the solution approaches, SLP could not solve the programs other than the deterministic one while PSO-MC could find at least good solutions, if not the global optima, for all the programs. Among the main decision variables, the stochastic programs resulted in a reduced size of irrigation district compared with that obtained by the deterministic program. Moreover, the programs using stochastic orders other than a simple expected value converged at solutions different from the solution reached by the expected value-based program.
机译：本文探讨了低不确定性和随机顺序类型（用于比较随机变量）对水库多作物灌溉区系统优化设计的影响。开发了四个具有经济目标函数的非线性数学程序，包括确定性，具有期望值顺序的随机EXP，具有随机优势度（SD）顺序的随机SD和具有预期增益置信极限（EGCL）顺序的随机EGCL。然后，选择了结合线性粒子群优化（PSO）算法和蒙特卡罗模拟（MC）的连续线性规划（SLP）和PSO-MC的方法来求解程序。以伊朗加兹温省的Hajiarab灌溉区为例，对使用不同程序和解决方案获得的结果进行了分析和比较。在解决方案方法中，SLP除了确定性解决方案之外无法解决其他程序，而PSO-MC可以为所有程序找到至少很好的解决方案，即使不是全局最优。在主要决策变量中，与确定性程序相比，随机程序导致灌溉区面积减少。此外，使用随机订单而不是简单期望值的程序收敛于与基于期望值的程序所达到的解决方案不同的解决方案。

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