Modeling the simple assembly line balancing (SALB) problem has covered a wide range of real-world applications. The recent advances in optimization problems have created the opportunities to tackle more challenging problems. This paper presents a multi-objective decision making problem to consider two objectives, cost and cycle time, for simple assembly line balancing. The problem is formulated as a mixed integer nonlinear optimization and the proposed study of this paper uses two metaheuristics to solve the resulted problem on some benchmark problems. The preliminary results have indicated that multi objective particle swarm optimization (MOPSO) has provided better quality solutions while the hybrid method based on MOPSO and simulated annealing has yielded more non-dominated Pareto solutions.Growing Science Ltd. All rights reserved. 7

In this paper, a concurrent planning of production and distribution is considered for manufacturers. In the production section production machines with a specific capacity that has the possibility of process multiple tasks simultaneously are intended and the tasks have the desired size and processing time and the overall size of the tasks within each category does not exceed the capacity of the machine. Also in distribution section the vehicles have specified capacity. In this study, by using meta-heuristic Genetics Algorithm the production problem is solved and in genetic algorithms to obtain better solutions help operators crossover and mutation has been taken. Results show that by increasing the size of the issue of genetic algorithms nearly optimum solutions and provides a shorter running time.

Given the competitive environment in the global market in recent years, organizations need to plan for increased profitability and optimize their performance. Planning for an appropriate product mix plays essential role for the success of most production units. This paper applies analytical network process (ANP) approach for product mix planning for a part supplier in Iran.