Immune optimization algorithm for constrained nonlinear multiobjective optimization problems
Applied Soft Computing
Expert Systems with Applications: An International Journal
A co-evolving decision tree classification method
Expert Systems with Applications: An International Journal
Negative selection based immune optimization
Advances in Engineering Software
Intelligent multi-criteria fuzzy group decision-making for situation assessments
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special issue on BISCSE 2005 " Forging the Frontiers" Part II
Expert Systems with Applications: An International Journal
Made-to-Measure Technologies for an Online Clothing Store
IEEE Computer Graphics and Applications
Evolutionary multi criteria design optimization of robot grippers
Applied Soft Computing
Ontology based personalized route planning system using a multi-criteria decision making approach
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
A competitive-cooperative coevolutionary paradigm for dynamic multiobjective optimization
IEEE Transactions on Evolutionary Computation - Special issue on computational finance and economics
Vaccine-enhanced artificial immune system for multimodal function optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Visual Learning by Evolutionary and Coevolutionary Feature Synthesis
IEEE Transactions on Evolutionary Computation
An information delivery model for banking business
International Journal of Information Management: The Journal for Information Professionals
Hi-index | 12.05 |
In this paper, we propose a co-evolutionary immune algorithm for the multi-criteria decision making (MCDM) model, and use the model to solve the large scale garment matching problem. Size fitting problem is a main obstacle to large scale garment sales and online sales because it is difficult to find the fit garments by the general size information. This study regards the fit garment matching problem as a MCDM model with the constraints of size satisfaction. An immune co-evolutionary algorithm is used to search the fit garments from the candidate garments in the stock. The garments in the stock are taken as antibodies and the customer request as antigen. The concepts of ideal garment and loose garment are virtual garment to model the customer request. Two affinity measures including dominance affinity and distance affinity are defined to represent the similarity of antibody to antibody and that of antibody to antigen. Correspondingly, the fit garments are chosen by two methods: the Pareto optimal garments by the MCDM solving algorithm, and the optimal garments with the minimal distance affinity to the ideal garments. An evaluation model on garments is proposed to evaluate the fit garments by the affinity measures. Based on the experiment data from the effective study of detail factors of female trousers, the proposed model and algorithm demonstrate to be a feasible and effective attempt aiming at a valuable problem and provide the key tool for garment store sale system or online garment order system to support accurate garment size matching.