A Lagrangian relaxation algorithm for optimizing a bi-objective agro-supply chain model considering CO 2 emissions
作者： Seyed Hamid Reza Pasandideh , Fatemeh Keshavarz-Ghorbani
DOI: 10.1007/S10479-021-03936-1
关键词: Context (language use) 、 Robust optimization 、 Purchasing 、 Linear programming 、 Lagrangian relaxation 、 Total cost 、 Algorithm 、 Computer science 、 Perishability
摘要: In this research, an agro-supply chain in the context of both economic and environmental issues has been investigated. To end, a bi-objective model is formulated as mixed-integer linear programming that aims to minimize total costs CO2 emissions. It generates integration between purchasing, transporting, storing decisions, considering specific characteristics agro-products such seasonality, perishability, uncertainty. This study provides different set temperature conditions for preserving products from spoilage. addition, robust optimization approach used tackle uncertainty paper. Then, $$\varepsilon$$ -constraint method convert single one. solve problem, Lagrangian relaxation algorithm applied efficient giving lower bounds original problem estimating upper bounds. At real case presented give valuable insight via assessing impacts system costs.
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