Fuzzy Modeling for Low-Carbon Dynamic Procurement Problem

Fuzzy Modeling for Low-Carbon Dynamic Procurement Problem The importance of effective and efficient procurement in the dynamic business environment cannot be neglected for overall performance of a firm. However, the parameters such as demand and availability of various resources are difficult to estimate with certainty. Thus, such uncertain parameters make it difficult to model lot-sizing procurement problem. Moreover, due to current environmental concerns the procurement problem must also address carbon emissions caused during procurement process. Therefore, this paper is an attempt to address the decision making for a low-carbon dynamic procurement problem for multi-products from multiple sources through multi-carriers in multi-period using fuzzy programming. In this paper, a fuzzy mixed integer linear program (FMILP) is proposed to obtain low-carbon optimal order allocation, supplier and carrier selection in the presence of fuzzy demand, fuzzy carrier and supplier capacities, and carbon emissions. The proposed FMILP is solved in LINGO 10. The working methodology of the proposed model is demonstrated using two illustrative examples. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Fuzzy Systems Springer Journals

Fuzzy Modeling for Low-Carbon Dynamic Procurement Problem

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Springer Berlin Heidelberg
Copyright © 2016 by Taiwan Fuzzy Systems Association and Springer-Verlag Berlin Heidelberg
Engineering; Computational Intelligence; Artificial Intelligence (incl. Robotics); Operations Research, Management Science
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