Multi-Level Decision Making | springerprofessional.de

Springer Professional

Top

2015 | Book

Read chapter Read first chapter

Multi-Level Decision Making

Models, Methods and Applications

Authors: Guangquan Zhang, Jie Lu, Ya Gao

Publisher: Springer Berlin Heidelberg

Book Series : Intelligent Systems Reference Library

Part of: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

Login to get access

About this book

This monograph presents new developments in multi-level decision-making theory, technique and method in both modeling and solution issues. It especially presents how a decision support system can support managers in reaching a solution to a multi-level decision problem in practice.

This monograph combines decision theories, methods, algorithms and applications effectively. It discusses in detail the models and solution algorithms of each issue of bi-level and tri-level decision-making, such as multi-leaders, multi-followers, multi-objectives, rule-set-based, and fuzzy parameters.

Potential readers include organizational managers and practicing professionals, who can use the methods and software provided to solve their real decision problems; PhD students and researchers in the areas of bi-level and multi-level decision-making and decision support systems; students at an advanced undergraduate, master’s level in information systems, business administration, or the application of computer science.

Advertisement

Table of Contents

Frontmatter

Bi-level Decision Making

Frontmatter

Chapter 1. Decision Making and Decision Support Systems

Abstract

This book addresses an important decision making area—multi-level decision-making. To help readers understand the following chapters of this book, this chapter presents fundamental concepts, models, and techniques of decision making and decision support systems (DSS), thus providing an introduction for the remaining chapters of this book.

Guangquan Zhang, Jie Lu, Ya Gao

Chapter 2. Optimization Models

Abstract

To model and solve a bi-level or multi-level optimization problem, we have to first understand basic single-level optimization models and related solution methods. This chapter introduces related concepts, models and solution methods of basic single-level optimization including linear programming, non-linear programming, multi-objective programming, goal programming, Stackelberg game theory, and particle swarm optimization. These knowledge will be used in the rest of the book.

Guangquan Zhang, Jie Lu, Ya Gao

Chapter 3. Bi-level Programming Models and Algorithms

Abstract

This chapter introduces basic definitions, theorems, models and algorithms for bi-level programming (bi-level decision-making) and also basic models of multi-level programming, which will be used in the remaining chapters of this book.

Guangquan Zhang, Jie Lu, Ya Gao

Multi-level Multi-follower Decision Making

Frontmatter

Chapter 4. Bi-level Multi-follower Decision Making

Abstract

A bi-level decision problem may involve multiple decision entities (decision units or decision makers) at the lower level, and these followers may have different reactions for a possible decision made by the leader.

Guangquan Zhang, Jie Lu, Ya Gao

Chapter 5. Bi-level Multi-leader Decision Making

Abstract

In real-world applications, a bi-level decision problem may involve multiple decision entities on the upper level, that is, the bi-level decision problem has multiple leaders. The leaders may have their individual decision variables, objective functions and/or constraint conditions. This kind of bi-level decision problem is called a bi-level multi-leader (BLML) decision problem.

Guangquan Zhang, Jie Lu, Ya Gao

Chapter 6. Tri-level Multi-follower Decision Making

Abstract

In a tri-level hierarchical decision problem, each decision entity at one level has its objective, constraints and decision variables affected in part by the decision entities at the other two levels. The choice of values for its variables may allow it to influence the decisions made at other levels, and thereby improve its own objective. We called this a tri-level decision problem. When multiple decision entities are involved at the middle and bottom levels, the top-level entity’s decision will be affected not only by these followers’ individual reactions but also by the relationships among the followers. We call this problem a tri-level multi-follower (TLMF) decision.

Guangquan Zhang, Jie Lu, Ya Gao

Fuzzy Multi-level Decision Making

Frontmatter

Chapter 7. Fuzzy Bi-level Decision Making

Abstract

Various uncertain issues naturally appear in organizational bi-level decision problems. Fuzzy sets and fuzzy systems can be used to handle uncertainties. This chapter introduces related definitions, theorems and models of fuzzy bi-level decision-making (FBLDM) and develops related algorithms to solve the uncertain issues in bi-level decision-making.

Guangquan Zhang, Jie Lu, Ya Gao

Chapter 8. Fuzzy Multi-objective Bi-level Decision Making

Abstract

In Chap. 7, we presented a set of solution approaches and related algorithms to solve a fuzzy bi-level programming problem. This chapter extends the results given in Chap. 7 by adding the capability to handle the multi-objective issue, that is, the leader, or the follower, or both have multiple objectives.

Guangquan Zhang, Jie Lu, Ya Gao

Chapter 9. Fuzzy Multi-objective Bi-level Goal Programming

Abstract

In Chap. 8, we presented the definitions, solutions, and algorithms for the fuzzy multi-objective bi-level programming (FMO-BLP) problems. This chapter still addresses the fuzzy multi-objective bi-level problem but applies a goal programming approach. We call it fuzzy multi-objective bi-level goal programming (FMO-BLGP). This chapter will discuss related definitions, solution concepts, and algorithms for the FMO-BLGP problem and will focus on the linear version of the FMO-BLGP problem. First, a fuzzy ranking method is used to give a mathematical definition for a FMO-BLGP problem, and then, based on a fuzzy vectors distance measure definition, a fuzzy bi-level goal programming (FBLGP) model is proposed. An algorithm for solving the FMO-BLGP problem is also developed.

Guangquan Zhang, Jie Lu, Ya Gao

Rule-set-based Bi-level Decision Making

Frontmatter

Chapter 10. Rule-Set-Based Bi-level Decision Making

Abstract

As discussed in previous chapters, bi-level decision-making problems are normally modeled by bi-level programming.

Guangquan Zhang, Jie Lu, Ya Gao

Multi-level Decision Support Systems and Applications

Frontmatter

Chapter 11. Fuzzy Bi-level and Tri-level Decision Support Systems

Abstract

This chapter presents two multi-level decision support systems that implement related algorithms developed in previous chapters to support decision making in practice.

Guangquan Zhang, Jie Lu, Ya Gao

Chapter 12. Bi-level Programming for Competitive Strategic Bidding Optimization in Electricity Markets

Abstract

We focus on the application of bi-level programming in electricity markets (power market) in this chapter. Competitive strategic bidding optimization of electric power plants (companies) is becoming one of the key issues in electricity markets. This chapter presents a strategic bidding optimization technique developed by applying the bi-level programming. By analyzing the strategic bidding behavior of power plants, we understand that this bidding problem includes several power plants and only one market operator respectively known as multiple leaders and single follower.

Guangquan Zhang, Jie Lu, Ya Gao

Chapter 13. Bi-level Pricing and Replenishment in Supply Chains

Abstract

Effective pricing and replenishment strategies in supply chain management are the keys to business success. Notably, with rapid technological innovation and strong competition in hi-tech industries such as computer and communication organizations, the upstream component price and the down-stream product cost usually decline significantly with time. As a result, effective pricing and replenishment decision models are very important in supply chain management. This chapter first establishes a bi-level pricing and replenishment strategy optimization model in hi-tech industry. Then, two bi-level pricing models for pricing problems, in which the buyer and the vendor in a supply chain are respectively designated as the leader and the follower, are presented. Experiments illustrate that bi-level decision techniques can solve problems defined by these models and can achieve a profit increase under some situations, compared with the existing methods.

Guangquan Zhang, Jie Lu, Ya Gao

Chapter 14. Bi-level Decision Making in Railway Transportation Management

Abstract

Transportation management is an important application field of bi-level decision-making. For example, transportation facilities, resources planning and moving, as well as staff relocation all involve sub-optimization and optimization problems, that is, the decision entities are often at two decision levels. This chapter presents two real applications of the bi-level decision techniques in railway transportation management.

Guangquan Zhang, Jie Lu, Ya Gao

Backmatter

Title: Multi-Level Decision Making
Authors: Guangquan Zhang
Jie Lu
Ya Gao
Copyright Year: 2015
Publisher: Springer Berlin Heidelberg
Electronic ISBN: 978-3-662-46059-7
Print ISBN: 978-3-662-46058-0
DOI: https://doi.org/10.1007/978-3-662-46059-7

Premium Partner