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Implementing the effective and efficient planning methods is a critical means to gain competitiveness for the decision-maker of manufacturing enterprise in today's global market. We proposed adaptive response mechanism based on the hybrid simulation and optimization (ARESOP) that provides a formal bridge between long-term plans and shortterm schedules. ARESOP is composed of knowledge generator (KG) based optimization mechanism and knowledge simulator (KS) based discrete event system and performance monitor based rule-based heuristic mechanism. The KG selects the optimal plan of control parameters based on the estimated behavior of the system and forecasting demand from legacy system like ERP and MRP. The KS evaluate the plan from KS and check whether it is acceptable. Feedback control loops are employed at higher level to evaluate the performance and update the control parameters. Also, The comparison between the optimal and actual values of the two monitoring variables: demand and production release rates is performed by Performance Monitor (PM) module. The times at which performance monitoring is done can be periodic (performance is sampled at regular time intervals, event-based (performance is sampled upon detection of certain event such as machine breakdown, urgent order arrivals)). The significant advantage of the proposed method is shown. For a design and implementation, the data model and architecture of ARESOP is presented in this paper.