A model based on a quadratic assignment problem (QAP) is proposed to design a process layout. The objective function of proposed model has three main parts, as: a) maximising the profit of each product; b) minimising stored keeping materials; c) minimising total layout cost. The demand requirement and production capacity are also considered as set of constraints. Eventually, as the global optimum solution is hard to find for the proposed model, a genetic algorithm (GA) is proposed to solve the model. The performance of proposed GA was compared with other well-known algorithms, i.e., simulated annealing (SA) algorithm and tabu search (TS) on several benchmark instances of QAP as well as a series of simulated random large scale instances. The comparison reveals the promising results of GA over SA, and TS.