Optimizing Ready Mixed Concrete Production Plants via a Genetic Algorithm Approach Used for Batching Plant Equipment Layout

Abstract

Iranian construction industry confronts a remarkable increase in concrete consumption. Practitioners believe that conventional on-site construction methods could not be used widely especially in large cities, because of the environmental, technical, and economic considerations. These days central mix plants or batching plants are widely used in ready mixed concrete production plants. However, these plants are criticized for low productivity, poor safety records, and high amount of land space used. The overall concrete production process can be improved by means of a layout optimization effort. An effective layout plan can directly improve the efficiency of the whole process of concrete production. This paper describes the findings of a survey of Iranian ready mixed plants in order to minimize the land space used by the equipment of batching plants. The problem of batching plant optimization was formulated and a genetic evolutionary algorithm was developed in MATLAB 7.1 in order to facilitate the optimization process. The efficiency of the proposed algorithm is demonstrated with reference to the time and land space used. Applying the model in a case study shows that the model is practicable, and it significantly reduces the land space used while improving other criteria.