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녹색물류에서 탄소배출을 고려한 최적화 모델에 대한 연구
정광헌 중앙대학교 한국전자무역연구소 2018 전자무역연구 Vol.16 No.3
Purpose: In this paper, we review the most recent literature on optimization models for carbon emission regulations. Currently, logistics and manufacturing companies must consider operational decisions on reducing carbon emissions that are emitted during production, transportation, and warehousing, while minimizing the total cost of production and inventory. Optimization models and methodologies have been developed to tackle this conflicting problem. The purpose of this paper is to summarize the results based on two basic models (EOQ and the lot-sizing problem), and to propose future directions of research. Composition/Logic: This paper is organized as follows. Chapter 1 begins with an overview of the research and the objective of this paper. In Chapter 2, we provide two basic optimization models, EOQ and the lot-sizing problem, and describe three kinds of regulations of carbon emissions. Chapter 3 summarizes optimization models extended from EOQ and lot-sizing models and managerial implications from the theoretical results. In Chapter 4, we propose three directions for future research based on a review of Chapter 3. Chapter 5 provides the conclusions of the paper. Findings: The summary of optimization literature shows that EOQ and lot sizing are the fundamental models for considering carbon emission regulations and that optimal solutions have similar characteristics. In particular, differences between optimization models on three main regulations such as cap, tax, and cap-and-trade are illustrated using mathematical expressions. We also propose potential research topics such as decisions regarding carbon emission reductions and extensions of vehicle routing problems. Originality/Value: This paper contributes a review of the extensive literature on optimization models for carbon emissions for readers who are not familiar with optimization. Based on the literature review, we propose three directions for future research on optimization of carbon emissions.
0-1 Mixed-Integer Bilinear Covering Sets에 대한 Lifted Bilinear Cover Inequalities의 Separation
정광헌 한국경영과학회 2019 韓國經營科學會誌 Vol.44 No.1
In this paper, we consider a computational study to evaluate the strength of Lifted Bilinear Cover (LBC) inequality for 0-1 Mixed-Integer Bilinear Covering Set. In particular, we develop a separation algorithm for LBC inequality to find the most violated cut by solving a simple optimization problem. After testing a separation algorithm on randomly generated instances, we provide numerical results that show LBC inequalities can help solve a bilinear optimization problem faster.