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Due to the desire of almost all departments of business organizations to be interconnected and to make data accessible at any time and any place, more and more multi-agent systems are applied to business management. As numerous agents are roaming through the Internet, they compete for the limited resource to achieve their goal. In the end, some of them will succeed, while the others will fail. However, when agents are initially created, they have little knowledge and experience with relatively lower capability. They should also strive to adapt themselves to the changing environment. It is advantageous if they have the ability to learn and evolve. This paper addresses evolution of intelligent agents in virtual enterprises. Agent fitness and fuzzy multi-criteria decision-making approach are proposed as evolution mechanisms, and fuzzy soft goal is introduced to facilitate the evolution process. Genetic programming operators are employed to restructure agents in the proposed multi-agent evolution cycle. We conduct a series of experiments to determine the most successful strategies and to see how and when these strategies evolve depending on the context and negotiation stance of the agent’s opponent.