Genetic algorithms are applied to the multiple products and multiple periods inventory lot-sizing problem with supplier selection under storage capacity. The objective of this research is to calculate the optimal inventory lot-sizing for each supplier and minimize the total inventory cost which includes joint purchase cost of the products transaction cost for the suppliers and holding cost for remaining inventory. It is assumed that demand of multiple products is known over a planning horizon. The problem is formulated as a mixed integer programming and is solved with genetic algorithms. Finally numerical example is provided to illustrate the solution procedure. The results determine what products to order in what quantities with which suppliers in which periods.

Proportional plus integral controller has been widely used in permanent magnet synchronous motor (PMSM) drive system due to its simple structure while achieving zero steady-state error. However finding out the optimal parameters of the controller is not an easy task. For this reason this paper presents an automated optimization of proportional plus integral controller for permanent magnet synchronous motor drive system using genetic algorithms. Simulation and experimental results verify the effectiveness than ones of the trial and error method.

This research considers the vehicle routing problem in a specific bakery making company where is located in Bangkok. This company has to produce and deliver the bakeries to its customers everyday. Until now this mentioned company generates the delivery’s route by using the experience taken from the company’s truck driver. The company has to daily use the route with unnecessary long distances. According to the given statement this research aims to develop algorithm to generate the delivery route for this company by using the Genetic Algorithm in order to minimize the transportation distances.