Cutting-edge technologies and optimization frameworks for energy efficiency enhancement of the entire domestic hot water (DHW) chain are crucial to fulfill the ambitious goals of the future building regulations. In this context, the present study establishes a multi-objective optimization framework for the DHW network in a typical residential building, in which the hot water is supplied by a PV-BESS driven air source heat pump system relying on the thermal energy storage (TES) to decouple energy production and demand. Emphasizing on the role of in-building control strategies and user behavior, the optimization algorithm employs the response surface methodology (RSM) with central composite design (CCD). It seeks to simultaneously minimize the total energy use for DHW production and total heat loss from the DHW network, while maximizing the temperature of delivered hot water to users as well as the TES mean temperature. To examine interactions in components of the DHW network, dynamic simulations are carried out by developing a TRNSYS model coupled to a MATLAB code. The latter generates the hourly DHW consumption profiles using Gaussian distribution. It is shown that the developed optimization framework strikes a balance between conflictive design factors to meet the targets of multi-criteria optimization. The variable TES set-point is found to be the most influential factor in terms of providing hot water at a higher temperature to users. Furthermore, adjusting the activation time (and flow rate) of recirculating loop and the TES charging time slots in accordance with the user behavior (draw-off) and peak consumption timespans demonstrate a significant impact on minimizing either the total energy use or thermal loss.