The purpose of present study is twofold. Firstly, this introduces a bi-objective closed-loop supply chain (CLSC) network by deliberating on farming of herbs and production plus distribution of associated herbal medicines in manufacturing-chain layer. Reverse-chain layer (RC-layer) recycles used substrates and unused herbs, thus producing biofuels and casing soil. Though majority of well-established CLSC models comprise sole pecuniary objective function, this aims to validates the economic self-reliance of RC-layer. Besides, Governments pay the subsidy to various entities, including the growers to encourage countrywide farming of herbs and the biofuels-plants for the extent of clean fuel produced. Thus, two different partners of same network earn subsidy without analysing trade-off. Secondly, this study develops an emended minmax method based interactive bi-objective optimization algorithm by employing absolute difference function and newly introduced semi-autonomized desired levels in real-life oriented T-environment. In pessimistic business scenario, whereas proposed model turns infeasible in classical interactive fuzzy multi-objective optimization algorithm, proposed algorithm determines corresponding Pareto optimal solution. In optimistic business scenario, optimal net profits to both layers of proposed model are more desirable than respective goals in proposed algorithm. Vulnerability analysis of twelve parameters to proposed model plus twelve subfigures pleads legislators to offer more subsidy to biofuels-plants and slightly lesser to growers; and to enact regulations to intensify the recycling of discarded substrates and herbs, thereby ensuring financial feasibility of RC-layer. Again, reduced subsidy to biofuels-plants and little more subsidy to growers, plus multi-angled modernization of all partners except landfills elevate the profitability of proposed network.
Bibliographical noteFunding Information:
This research was supported by the Yonsei University Research Fund of 2019 (2019-22-0198). The first author is highly indebted and thankful to Prof. S. Alam, Dept. of Mathematics, IIEST, Shibpur, India, for his kind assistance in coding.
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