Papers by Author: Guo Hai Zhang

Abstract: This paper presents a new kind of retrieval and clustering solution for multiple disciplines design knowledge during complex product development. The main contributions of this study can be focused on four points: The first is to distinguish the concepts and contents of ontology theories and semantic web. The second is to map the distinction and relationship between concepts to similarity and correlation of product design knowledge. The substances of conceptual hierarchy are introduced and their formal descriptions are given in the article. The third is to explore the specific calculation methods for semantic similarity and relevancy using the above theories and approaches. Finally, a model for design knowledge retrieval if proposed, and the tactics for knowledge retrieval and clustering are given.

Abstract: This paper presents a new model of multi-discipline knowledge reasoning for collaborative design. The main contributions of this study can be focused on three points: The first is to clarify the concepts and contents of the polychromatic sets and polychromatic graph. The second is to put forward the knowledge reasoning model for multi-discipline knowledge based on polychromatic sets. Finally, the mathematical solutions for contour matrix, the causal relationship between the adjacent and the same knowledge patterns are given.

Abstract: This paper presents a new kind of scheduling solution for multiple design tasks in networked developing environments. The main contributions of this study can be focused on three points: The first is to distinguish the concepts and contents of the task scheduling in the networked developing environments. The second is to construct a game-theory mathematical model to deal with this new multiple design tasks scheduling problem. In the presented mathematical model, the players, strategies and payoff are given separately. Therefore, obtaining the optimal scheduling results is determined by the Nash equilibrium (NE) point of this game. In order to find the NE point, a genetic algorithm (GA)-based solution algorithm to solve this mathematical model is proposed. Finally, a numerical case study is presented to demonstrate the feasibility of the methods.