Sustainable ordering policies for non-instantaneous deteriorating items under carbon emission and multi-trade-credit-policies

Sunil Tiwari, Waqas Ahmed, Biswajit Sarkar

Research output: Contribution to journalArticlepeer-review

77 Citations (Scopus)


In the current business market, organizations have to work mutually to control the rising level of carbon emission parallel with long-lasting financial benefits. Green inventory management reduces the environmental impacts of a business without lacking its profit. This study demonstrates a fuzzy green inventory model having non-instantaneous deteriorating products which help the organizations for maximization of total annual profit under different conditions of trade-credit-policies along with minimizing carbon for a cleaner environment. The paper discusses all the potential cases, which may occur in green inventory models with carbon emission cost under different allowable delay-in-payments. Here, the demand rate is taken as dependent on selling price. In addition, shortages are allowable and are completely backlogged. The whole profit is calculated from the retailer's perspective. In this model, demand, as well as deterioration rates, are considered as a triangular fuzzy number. The objective has to evaluate sustainable optimal ordering strategies for retailers, which maximize the entire annual profit and minimize the carbon emission. The various possible scenarios are discussed in detail to get the relevant profit of a retailer. The validity of the established model is proved by presenting a numerical experiment. Sensitivity analysis of this study is also exemplified to verify its factual practice.

Original languageEnglish
Article number118183
JournalJournal of Cleaner Production
Publication statusPublished - 2019 Dec 10

Bibliographical note

Publisher Copyright:
© 2019 Elsevier Ltd

All Science Journal Classification (ASJC) codes

  • Renewable Energy, Sustainability and the Environment
  • General Environmental Science
  • Strategy and Management
  • Industrial and Manufacturing Engineering


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