Search results for " Demand Forecasting"
showing 2 items of 2 documents
Training Artificial Neural Networks With Improved Particle Swarm Optimization
2020
Particle Swarm Optimization (PSO) is popular for solving complex optimization problems. However, it easily traps in local minima. Authors modify the traditional PSO algorithm by adding an extra step called PSO-Shock. The PSO-Shock algorithm initiates similar to the PSO algorithm. Once it traps in a local minimum, it is detected by counting stall generations. When stall generation accumulates to a prespecified value, particles are perturbed. This helps particles to find better solutions than the current local minimum they found. The behavior of PSO-Shock algorithm is studied using a known: Schwefel's function. With promising performance on the Schwefel's function, PSO-Shock algorithm is util…
The Impact Of Demand And Inventory Management Policies On Bullwhip Effect In Production Networks
2004
The bullwhip effect is a phenomenon consisting in variance amplification of orders as they move up a supply chain. The immediate bullwhip effect consequences are the increase of inventory costs, poor custoiner services and inefficient utilization of resources due to the difficulties of production planning activities in highly variable conditions. There are many factors that cause the bullwhip effect, but if is particularly due to demand forecasting and inventory management policies. In this paper the impact on bullwhip effect of different policies to manage demand and inventories has been evaluated through discrete event simulation, using the ARENA (R) simulation package.