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Mathematics 2019, 7(3), 234; https://doi.org/10.3390/math7030234

Low Carbon Supply Chain Coordination for Imperfect Quality Deteriorating Items

1
Department of Industrial and Systems Engineering, Chung Yuan Christian University, 200 Chung-Pei Rd., 32023 Chung-li, Taoyuan, Taiwan
2
Department of Industrial Engineering, Universitas Atma Jaya Yogyakarta, Jl. Babarsari 43, 55281 Yogyakarta, Indonesia
3
Department of Industrial Engineering, Petra Christian University, Surabaya, East Java 60236, Indonesia
*
Author to whom correspondence should be addressed.
Received: 19 January 2019 / Revised: 18 February 2019 / Accepted: 20 February 2019 / Published: 5 March 2019
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Abstract

Nowadays, many countries have implemented carbon pricing policies. Hence, the industry adapts to this policy while striving for its main goal of maximizing financial benefits. Here, we study a single manufacturer–retailer inventory decision considering carbon emission cost and item deterioration for an imperfect production system. This study examines two models considering two cases of quality inspection. The first is when the buyer performs the quality inspection, and the second is when the quality inspection becomes the vendor’s responsibility so that no defective products are passed to the buyer. Carbon emission costs are incorporated under a carbon tax policy, and we consider the carbon footprint from transporting and warehousing the items. The objective is to jointly optimize the delivery quantity and number of deliveries per production cycle that minimize the total cost and reduce the total carbon emissions. This study provides solution procedures to solve the models, as well as two numerical examples. View Full-Text
Keywords: supply chain inventory; imperfect quality; inspection; carbon emission; deteriorating items supply chain inventory; imperfect quality; inspection; carbon emission; deteriorating items
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Daryanto, Y.; Wee, H.M.; Widyadana, G.A. Low Carbon Supply Chain Coordination for Imperfect Quality Deteriorating Items. Mathematics 2019, 7, 234.

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