A Branching Process for Convergent Product Optimization

Ermia Aghasi,Mansour Momeni,Mohammad Ali Shah Hoseini

doi:10.22158/rem.v2n4p1

Ermia Aghasi, Mansour Momeni + Show 1 more

Open Access

https://doi.org/10.22158/rem.v2n4p1

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Abstract

We consider a discrete time branching process where the population consists of k types of convergent products, an action is chosen for that which affects the lifetime, the number and types of its functions, and the profit received. The problem of maximizing the expected profit is shown to be equivalent to a generalized Markov decision problem of maximizing the expected profit is shown to be equivalent to a generalized Markov decision problem where the transition matrices are non-negative but not necessarily sub stochastic.

Highlights

Research over the past 30 years has shown that the New Product Development (NPD) process is based on a series of development stages that are interpolated by a series of evaluative stages
This paper is primarily concerned with the problem of controlling a discrete time branching process where the population consists of k, a finite number, types of convergent products
There we show that some policy of control of a simple form is optimal over a much wider class of policies, and we show how to compute such an optimal policy by solving a second Markov decision problem whose ( k k ) transition matrices are nonnegative but not necessarily sub stochastic

Summary

Introduction

Research over the past 30 years has shown that the NPD process is based on a series of development stages that are interpolated by a series of evaluative stages. Other authors measured the overall satisfaction of project managers with the new product development process and results. This paper is primarily concerned with the problem of controlling a discrete time branching process where the population consists of k, a finite number, types of convergent products.

Results

Conclusion