Today’s competition in many manufacturing industries is leading companies to expand their product portfolio, which combined with the advanced technology present in modern production sites, raises the need for efficient production planning. Often times, purchasing new production machinery is not an option because of the increase in fixed costs. Hence, efforts are being directed towards technology and efficiency improvement.
On February 26th, Javier Lafuente, CEO of decide soluciones, together with IBM presents the webinar "Optimizing replenishment processes in the Fashion Industry".
Stochastic Optimization seeks the best decision in a scenario involving random events, those that depend on chance, whether those events are product prices, task durations, the number of people queueing at an ATM, the number of breakdowns in a fleet of trucks, or even the adoption of regulations.
In general, studying the properties of linear systems and their solution is much simpler than for non-linear systems. Throughout history, linearization of functions around certain values is a highly used technique to analyse the performance of non-linear systems.
In previous entries we saw there are cases in which Integer Linear Programming is not the most appropriate approach to solve routing problems, and we proposed the option of using metaheuristic algorithms to obtain feasible solutions, and in many cases close to the optimal solution.