An intelligent order allocation system for effective order fulfilment under changing customer demand

Abstract

In today's intense global competition, problems still exist under the umbrella of Just-in-Time application in the field of order management. The management of a firm usually faces difficulty in allocating stock to fulfil customer order, especially in the case of receiving a sudden change request from customers. In order to ease order allocation issues aroused by JIT, an intelligent system, namely, Intelligent Sales Order Handling System (ISOAS), is developed through the integration of fuzzy-AHP approach for decision making process in order allocation. This approach enables the selection of desired sales orders based on multiple criteria which may be quantitative or qualitative in nature, according to the judgment of scholars and domain experts. With ISOAS, customer orders are prioritized with respect to the values according to their performance under each decision making attributes. The degree of confidence of the decision judgements are quantified through the spread of fuzzy numbers with fuzzy pairwise comparison calculations. The approach can transform the fuzziness of human preference into the measurable number, enabling the operation of the AI-based system to assist humans in decision-making. An order allocation case study in a logistics department is demonstrated in this study. Results indicate an improved efficiency during the decision making process.