This paper addresses the economic dispatch challenge in integrated energy systems (IES) with high renewable energy source (RES) penetration, where existing models often neglect the quantification of RES uncertainty, leading to inefficiencies and instability. This paper proposes a novel information-energy co-optimization framework that integrates generalized information work to quantify RES uncertainty, which is incorporated into a multi-objective economic dispatch model. The framework jointly optimizes energy costs, information work costs, and exergy loss, supported by an enhanced NSGA-III algorithm with dynamic reference point adjustment and TOPSIS-based solution selection. Simulations on a modified 21-bus IES reveal that the proposed model reduces total costs under high RES uncertainty, while achieving a reduction in exergy loss across different scenarios.