Particle Swarm Optimization algorithm for optimization of utility systems in chemical processes

Different techniques for the optimization of utility systems have been developed in recent decades. The objective of this paper is to introduce a new mathematical programming model applied to the operational optimization for the utility system. Particle Swarm Optimization (PSO) presented by Kennedy has been described for solving mixed integer linear programming (MILP). It is a simple algorithm that seems to be effective for optimizing a wide range of functions, which a few parameters can be implemented easily. The case of utility system for the chemical process is also formulated as a MILP model where the mass and energy balances, the operational status of each unit, and the demand satisfaction of steam and electricity are defined. The target of the model is to minimize the utility costs. Current results are proved to be reliable, which implied that the current method is more effective and robust compared to the conventional method.