Decision models for managing demand and supply uncertainties in supply networks

Anssi Käki

Research output: ThesisDoctoral ThesisCollection of Articles

Abstract

Companies can use mathematical models to improve their decisions under uncertainty. This Dissertation focuses on sourcing and supply management decisions under i) uncertain demand of products or components and ii) uncertain capability of suppliers to deliver high-quality materials and services. Modern planning systems help automatize and optimize decision making in these areas, but most these systems are not good at accounting for uncertainties. However, in many industries, the effective management of demand and supply uncertainties is an important source of competitive advantage. Thus, there is a need for decision models that help managers analyze the impacts of uncertainties. The Dissertation develops methods based on stochastic optimization where both continuousand discrete (scenario-based) probability distributions are used to model demand and supplyuncertainties. Particular attention is given to the qualitative characteristics of distributionsand interdependencies between uncertainties. In addition, a static methodology for assessingdisruption risks in complex supply networks is presented. The Dissertation illustrates how the neglect of uncertainties can lead to sub-optimal decisionrecommendations, and, on the other hand, how a decision maker can better utilize decisionmodels by modeling the relevant uncertainties appropriately. The theoretical part iscomplemented with experimental results which show that subjects have significant difficultiesin making simple procurement decisions in the presence of demand and supply uncertainties,and that decision support tools can significantly improve their decision making in this area. The careful modeling of uncertainties yields robust decision recommendations that perform well in most or all uncertainty scenarios. By using the methodologies presented in Dissertation, managers can better manage the uncertainties in customer demand and suppliers' performance and material availability. This increases the competitiveness and capability to manage risks in an uncertain business environment.
Translated title of the contributionPäätöksentekomallit toimitusverkkojen kysyntä- ja toimitusepävarmuuksien hallinnassa
Original languageEnglish
QualificationDoctor's degree
Awarding Institution
  • Aalto University
Supervisors/Advisors
  • Salo, Ahti, Supervising Professor
  • Salo, Ahti, Thesis Advisor
  • Talluri, Srinivas, Thesis Advisor, External person
Publisher
Electronic ISBNs978-952-60-5607-4
Publication statusPublished - 2014
MoE publication typeG5 Doctoral dissertation (article)

Keywords

  • stochastic optimization
  • demand and supply uncertainties
  • scenarios
  • copula functions
  • supply management
  • newsvendor model
  • risk management

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