A New Multi Objective Optimization to Improve Growth Domestic Produce of Economic Using Metaheuristic Approaches: Case Study of Iraq Economic

Currently, optimization problems are some of the immediate concern in economics. Peoples’ need is fast diversifying, while resources remain limited. This phenomenon is called the Multi-Objective Optimization (MOO) problem. Current techniques are mostly grounded in redundancy, large size path, long processing time. At this point in time, economic problems can be solved by utilizing mathematical principles, and one of the most common and effective approach include metaheuristics as soft computing techniques approaches in the context of the development of significance based plan reduction in the growth domestic product (GDP). The indicators in this model can be utilized to assess the state of a nation’s economy. This paper will discuss metaheuristics as soft computing techniques such Ant Colony Optimization (ACO) and Artificial Bees Colony (ABC) in order to propose an effective solution in the reduction of the complexity of MOO in the economy via the determination of an efficient strategy (plan). Experimental results proved that the usage of metaheuristics as soft computing techniques approaches is effective and more promising that current techniques, while ABC is superior to ACO in the context of search time and the exploration of an efficient global strategy (plan).