Hybrid strategies using linear and piecewise-linear decision rules for multistage adaptive linear optimization

نویسندگان

چکیده

Decision rules offer a rich and tractable framework for solving certain classes of multistage adaptive optimization problems. Recent literature has shown the promise using linear nonlinear decision in which wait-and-see decisions are represented as functions, whose parameters variables to be optimized, underlying uncertain parameters. Despite this growing success, real-world stochastic problems can become computationally prohibitive when rules, some cases, ones. Consequently, that competitive trade-off between solution quality computational time more attractive. Whereas extant research always used homogeneous major contribution paper is exploration hybrid rules. We first verify empirically having higher uncertainty resolution or pieces early stages significant than it late terms quality. Then we conduct comprehensive study non-increasing (i.e., stages) non-decreasing illustrate cost. also demonstrate case where rule superior piecewise-linear within simulator environment, supports need assess obtained from look-ahead model rather just model's objective function value.

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ژورنال

عنوان ژورنال: European Journal of Operational Research

سال: 2021

ISSN: ['1872-6860', '0377-2217']

DOI: https://doi.org/10.1016/j.ejor.2020.08.054