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The typical business processes in building material equipment manufacturing enterprises are analyzed, and the framework and functional models of the tracking system for building material equipment manufacturing enterprises in the order lifecycle are presented. Based on the model, using a mobile agent and XML technology, the order tracking system’s framework is built for building material equipment manufacturing enterprises based on a mobile agent in the Aglet platform. The key technologies in the process of tracking the order lifecycle are introduced in detail. Finally, a prototype system is developed and used in an enterprise successfully, verifying the feasibility and availability of the system. [ABSTRACT FROM AUTHOR]

In this paper we give direct, inverse, and equivalence approximation theorems with unified Ditzian-Totik modulus [image omitted] (0 ≤ λ ≤ 1) for Meyer-Konig and Zeller operators. [ABSTRACT FROM AUTHOR]

Recently some classical operator quasi-interploants were introduced to obtain much faster convergence. P. Mache and D. H. Mache gave Bernstein quasi-interpolants and obtained approximation equivalence theorem with . In this article we extend above result with modulus which unified classical modulus and Ditzian-Totik modulus. [ABSTRACT FROM AUTHOR]

The characteristics of decentralization, diversification, and dynamics of outsourcing resources put forward higher requirements for the supplier selection in manufacturing enterprises. For building materials equipment manufacturing enterprises (BMEM), due to the complex product structure, the demand for outsourcing resources is very large. The traditional method is difficult to meet the needs of current outsourcer evaluation and selection. In order to solve the problem, this paper establishes an outsourcing supplier selection model based on the quality, price, delivery time, reliability, and availability of outsourced suppliers. And then, a hybrid supplier selection algorithm based on Analytic Hierarchy Process (AHP) and Particle Swarm Optimization (PSO) is designed in this paper. Finally, the model and algorithm are verified and analyzed in BMEM. The paper also compares the algorithm with genetic algorithm (GA) and ant colony optimization (ACO). The experimental results show that the model can effectively improve the effectiveness and reliability of outsourcing supplier selection. [ABSTRACT FROM AUTHOR]