Abstract
Article history: Received April 26 2016 Received in Revised Format August 16 2016 Accepted September 14 2016 Available online September 14 2016 The product-mix planning and the lot size decisions are some of the most fundamental research themes for the operations research community. The fact that markets have become more unpredictable has increaed the importance of these issues, rapidly. Currently, directors need to work with product-mix planning and lot size decision models by introducing stochastic variables related to the demands, lead times, etc. However, some real mathematical models involving stochastic variables are not capable of obtaining good solutions within short commuting times. Several heuristics and metaheuristics have been developed to deal with lot decisions problems, in order to obtain high quality results within short commuting times. Nevertheless, the search for an efficient model by considering product mix and deal size with stochastic demand is a prominent research area. This paper aims to develop a general model for the product-mix, and lot size decision within a stochastic demand environment, by introducing the Economic Value Added (EVA) as the objective function of a product portfolio selection. The proposed stochastic model has been solved by using a Sample Average Approximation (SAA) scheme. The proposed model obtains high quality results within acceptable computing times. © 2017 Growing Science Ltd. All rights reserved
Highlights
It is a huge challenge for companies to reach strategic decisions related to the production system
This paper aims to develop a general model for the product-mix, and lot size decision within a stochastic demand environment, by introducing the Economic Value Added (EVA) as the objective function of a product portfolio selection
The decisions of the stochastic model are defined in two steps by considering variability of the demand. It is first proposed as the objective function of the Stochastic Mixed Integer Linear Programming Model (SILP) model, the maximization of EVA, and the latter is defined as the economic value added generated by the company
Summary
It is a huge challenge for companies to reach strategic decisions related to the production system. The decision making process becomes very difficult due to the fact that companies usually do not have the tools to solve the problem of lot sizing and product-mix planning by considering the maximization of the profit of the companies. This decision affects both, the productivity and the profitability of them. The solution strategy used for the SILP model solution is known as Sample Average Approximation (SAA) This methodology has been proposed by Kleywegt et al (2002) and uses a scheme of sample averages by Monte Carlo Simulation for stochastic linear programming problems
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