Abstract: Significant time delays and energy inefficiencies are frequently caused by implementing Industrial Control Systems (ICS) in Industrial Wireless Sensor Networks (IWSN). To overcome these issues, this paper suggests two optimization techniques: Harris Hawk Optimization (HHO) and Gradient-Based Optimization (GBO). The GBO technique uses gradient data to optimize ICS deployment to reduce delay times and increase IWSN energy efficiency. The system achieves an efficient communication flow and minimizes transmission delays by incrementally altering the arrangement of ICS components based on gradient descent. The allocation of resources and the elimination of unnecessary data transmissions optimize energy use. Similarly, the HHO approach optimizes ICS deployment in terms of time delay reduction and energy economy by modeling the cooperative hunting approach of Harris Hawks. The HHO algorithm effectively balances exploration and exploitation to find the best deployment configurations. Extensive simulations assess the proposed method in simulation model ICS scenarios. The outcomes show how well GBO and HHO work to cut down on delays and increase energy effectiveness. The enhanced ICS deployment reduces time delays and uses less energy than traditional deployment techniques, improving IWSN performance.