A novel hybrid chaotic ant swarm algorithm for heat exchanger networks synthesis

• The chaotic ant swarm algorithm is proposed to avoid trapping into a local optimum.
• The organization variables update strategy makes full use of advantages of the chaotic search.
• The structure evolution strategy is developed to handle integer variables optimization.
• Overall three cases taken form the literatures are investigated with better optima.

The heat exchanger networks synthesis (HENS) still remains an open problem due to its combinatorial nature, which can easily result in suboptimal design and unacceptable calculation effort. In this paper, a novel hybrid chaotic ant swarm algorithm is proposed. The presented algorithm, which consists of a combination of chaotic ant swarm (CAS) algorithm, structure evolution strategy, local optimization strategy and organization variables update strategy, can simultaneously optimize continuous variables and integer variables. The CAS algorithm chaotically searches and generates new solutions in the given space, and subsequently the structure evolution strategy evolves the structures represented by the solutions and limits the search space. Furthermore, the local optimizing strategy and the organization variables update strategy are introduced to enhance the performance of the algorithm. The study of three different cases, found in the literature, revealed special search abilities in both structure space and continuous variable space.