Interval valued intuitionistic fuzzy sets
Fuzzy Sets and Systems
Information Sciences: an International Journal
An novel approach to supplier selection based on vague sets group decision
Expert Systems with Applications: An International Journal
Fuzzy Optimization and Decision Making
A method based on distance measure for interval-valued intuitionistic fuzzy group decision making
Information Sciences: an International Journal
Fuzzy Sets and Systems
A study of using RST to create the supplier selection model and decision-making rules
Expert Systems with Applications: An International Journal
Supplier selection and order allocation based on fuzzy SWOT analysis and fuzzy linear programming
Expert Systems with Applications: An International Journal
A weighted additive fuzzy programming approach for multi-criteria supplier selection
Expert Systems with Applications: An International Journal
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
Maximum Ambiguity-Based Sample Selection in Fuzzy Decision Tree Induction
IEEE Transactions on Knowledge and Data Engineering
Reliable Knowledge Discovery
A new intuitionistic fuzzy rough set approach for decision support
RSKT'12 Proceedings of the 7th international conference on Rough Sets and Knowledge Technology
A weighted multivariate Fuzzy C-Means method in interval-valued scientific production data
Expert Systems with Applications: An International Journal
Information Sciences: an International Journal
Hi-index | 12.05 |
We consider the issue of warehouse evaluation towards successful logistic and supply chain management. Suppose a company has managed a chain of owned warehouses, and now this company is in need of acquiring some new and profitable warehouse adding to its operation chain. A key business decisions here is how to choose the most profitable warehouses from a number of potential warehouses. In reality, the challenge is that the future profitability is unpredictable. Therefore, it is infeasible to rank potential warehouses directly for choice. To address such a problem, this paper proposes a new rule-based decision model. This model includes the following characteristics: (i) decision information is provided via interval-valued intuitionistic fuzzy values; (ii) multiple experts as a group of decision makers are involved; (iii) both subjective evaluations from experts and objective data of historical profitability are employed; (iv) both certain and uncertain information are exploited. The core decision mechanism is, making use of uncertain information of owned warehouses, to induce a collection of ''if...then...''rules, and subsequently to exploit these rules for prediction of preference orders of all potential warehouses. Therein, we develop and integrate multiple techniques for the purposes of (a) aggregation of uncertain information; (b) construction of pairwise comparison; (c) induction of certain and uncertain rules; and (d) decision rules exploitation. We finally elaborate our discussion with a numerical example illustrating the application of the proposed decision mechanism to supply-chain domain problems.