The Supply chain in manufacturing, distribution, and transportation

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Contents

Preface.................................................................................................. ix

Introduction......................................................................................... xi

About the Editors.................................................................................xv

Contributors........................................................................................xix

Review Board .................................................................................... xxiii

SECTION I INDUSTRIAL AND SERVICE APPLICATIONS

OF THE SUPPLY CHAIN

1 Multicriteria Decision Making in Ethanol Production

Problems: A Fuzzy Goal Programming Approach......................3

KENNETH D. LAWRENCE, DINESH R. PAI,

RONALD K. KLIMBERG AND SHEILA M. LAWRENCE

2 From Push to Pull: The Automation and Heuristic

Optimization of a Caseless Filler Line in the

Dairy Industry.............................................................................13

BRIAN W. SEGULIN

3 Optimization of Medical Services: The Supply Chain

and Ethical Implications ............................................................29

DANIEL J. MIORI AND VIRGINIA M. MIORI

4 Using Hierarchical Planning to Exploit Supply Chain

Flexibility: An Example from the Norwegian

Meat Industry ..............................................................................47

PETER SCHUTZ, ASGEIR TOMASGARD, ¨

AND KRISTIN TOLSTAD UGGEN

5 Transforming U.S. Army Supply Chains:

An Analytical Architecture for Management Innovation ........69

GREG H. PARLIER

v

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vi
Contents

SECTION II ANALYTIC PROBABILISTIC MODELS

OF SUPPLY CHAIN PROBLEMS

6 A Determination of the Optimal Level of Collaboration

between a Contractor and Its Suppliers under

Demand Uncertainty ..................................................................97

SEONG-HYUN NAM, JOHN VITTON,

AND HISASHI KURATA

7 Online Auction Models and Their Impact

on Sourcing and Supply Management ....................................121

JOHN F. KROS AND CHRISTOPHER M. KELLER

8 Analytical Models for Integrating Supplier Selection

and Inventory Decisions..........................................................133

BURCU B. KESKIN

9 Inventory Optimization of Small Business Supply

Chains with Stochastic Demand..............................................151

KATHLEEN CAMPBELL, GERARD CAMPAGNA,

ANTHONY COSTANZO, AND CHRISTOPHER MATTHEWS

SECTION III OPTIMIZATION MODELS OF SUPPLY

CHAIN PROBLEMS

10 A Dynamic Programming Approach to the Stochastic

Truckload Routing Problem.....................................................179

VIRGINIA M. MIORI

11 Modeling Data Envelopment Analysis (DEA)

Efficient Location/Allocation Decisions .................................205

RONALD K. KLIMBERG, SAMUEL J. RATICK,

VINAY TAVVA, SASANKA VUYYURU,

AND DANIEL MRAZIK

12 Sourcing Models for End-of-Use Products

in a Closed-Loop Supply Chain................................................219

KISHORE K. POCHAMPALLY AND SURENDRA M. GUPTA

13 A Bi-Objective Supply Chain Scheduling ................................243

TADEUSZ SAWIK

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Contents
vii

14 Applying Data Envelopment Analysis and Multiple

Objective Data Envelopment Analysis to Identify

Successful Pharmaceutical Companies ...................................277

RONALD K. KLIMBERG, GEORGE P. SILLUP,

GEORGE WEBSTER, HAROLD RAHMLOW,

AND KENNETH D. LAWRENCE

Index .................................................................................................297

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Preface

This volume is a blind-refereed, multi-authored volume. The objective of this volume

is to present state-of-the-art studies in the areas of manufacturing, distribution, and

transportation to solve significant problems within the supply chain integration

process. This volume focuses on research that integrates the problems of production,

distribution, and transportation.

Tactical models support the mid-level decision-making processes that typically

extend into a planning horizon of 6 to 18 months. The models featured address a

number of areas. High-level production schedules describe the equipment to be used

and the hours that a production plant will operate. Product sourcing models assign

customers to the most cost-efficient production plant or distribution center as a

source of their orders. Network alignment models assist in determining the products

to be produced in each production plant, and stored in each distribution center.

Additional tactical models focus on transportation operations with consistent

demand. These operations will create static shipment schedules designed to be fol￾lowed week after week. The physical layout of distribution centers is also a tactical

decision. The product lines stored may change by season, requiring reexamination

of product storage locations. The goal is the minimization of total distance traveled

within the distribution center.

The area of inventory planning is a tactical area that has been the subject of

substantial research. Inventory strategies begin with the determination of how much

inventory to carry and at what inventory level to reorder the products. At their

most complex level, inventory strategies address the possible postponement of final

production processes in order to reduce costs. This is most common when standard

subassemblies are used for many specialized final products. The subassemblies are

lower valued and therefore less expansive to carry. The final production is postponed

until an order has been placed for specific products.

Furthermore, operational models involve detailed or day-to-day operations and

scheduling processes. The planning horizon for these models ranges from a week to

several months. Manufacturing operations cannot effectively run without detailed

planning models that schedule the raw material and intermediate product shipments.

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x
Preface

These schedules feed into another class of models that schedules the production at

these manufacturing facilities. Production schedules include the changeover between

products and maintenance of equipment. In cases where multiple production lines

are employed, the scheduling task grows very quickly in complexity. Operational

planning in the transportation and distribution areas of the supply chain examine

the consolidation of small shipments and the breaking down of larger shipments

with the goal of cost-efficiency in transportation. In addition, models are addressed

that create low-cost truck routes and assignment of various capacity vehicles to these

routes. They also meet delivery time windows required by customers.

Both tactical and operational models rely on good quality forecasts of demand.

Stochastic customer demand, coordination of supply chain functions, and solution

algorithms are of a critical nature and are highlighted in this volume.

The overall integration of transportation, distribution, and production involves

the following crossovers:

Production and outbound transportation

Inbound transportation and production

Inbound transportation, production, and outbound transportation

This book is a compilation of scholarly research work involving the utilization of

the discussed supply chain concepts, which address a wide variety of organizational

issues. It is comprised of a variety of noteworthy works emanating not only from the

academic spectrum, but also from business practitioners on a more limited basis.

The book is divided into three sections:

Section I: “Industrial and Service Applications of the Supply Chain”

Section II: “Analytic Probabilistic Models of Supply Chain Problems”

Section III: “Optimization Models of Supply Chain Problems”

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Introduction

Section I: Industrial and Service Applications

of the Supply Chain

Chapter 1, “Multicriteria Decision Making in Ethanol Production Problems: A

Fuzzy Goal Programming Approach,” applies a multiple objective approach to the

optimization of the supply chain over the echelon of material sources, processing

mills, and customers for the production of ethanol and associated by-products. The

multiple objectives include cost minimization at all levels, as well as the minimization

of environmental impact resulting from ethanol production.

Chapter 2, “From Push to Pull: The Automation and Heuristic Optimization of a

Caseless Filler Line in the Dairy Industry,” applies cost minimization in the transition

of a dairy supply chain. The move from the manual “push” supply chain to automated

“pull” supply chain not only provided greatly improved internal efficiencies, but also

facilitated the opening of new customer channels for the dairy. Despite the fact that

supply chain management has been applied extensively across manufacturing and

production sectors, more traditional industries, such as the dairy industry, have

lagged.

Chapter 3, “Optimization of Medical Services: The Supply Chain and Ethical

Implications,” provides a positive basis for the resolution of ethical questions while

building an alternative “production style” supply chain for the health-care industry.

This new supply chain is simulated and validated for continuing work in optimiza￾tion. Manufacturing and service supply chain optimization models have always run

parallel paths with little investigation into the benefits of applying the opposing

techniques. While true in all sectors, it is especially the case in the health-care sector

where issues of ethical treatment of patients are paramount.

Chapter 4, “Using Hierarchical Planning to Exploit Supply Chain Flexibility:

An Example from the Norwegian Meat Industry,” provides a supply chain opti￾mization example from the Norwegian meat industry. One of the greatest challenges

in developing optimal solutions within the supply chain setting is the existence of

stochastic elements in the supply chain. Whether changes occur on a daily basis or

less frequently over time, a hierarchical approach to optimal supply chains offers

sufficient flexibility to manage these changes.

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xii
Introduction

Chapter 5, “Transforming U.S. Army Supply Chains: An Analytical Architecture

for Management Innovation,” addresses the need for the U.S. Army to transform

from the existing logistics approach to the challenges faced in the world today. It

examines the current structure, proposes alternative models, and highlights challenges

that will be faced in the ultimate transformation of the U.S. Army supply chains. It

is widely understood that the most challenging logistics operations exist within the

armed forces. Since World War II, operations research has played a significant role

in these operations.

Section II: Analytic Probabilistic Models

of Supply Chain Problems

Chapter 6, “A Determination of the Optimal Level of Collaboration between a

Contractor and Its Suppliers under Demand Uncertainty,” focuses on the analysis of

the collaboration level connected to demand uncertainty and its associated economic

costs, based on the number of suppliers utilized by a contractor to maximize the

supply chain profile.

Chapter 7, “Online Auction Models and Their Impact on Sourcing and Supply

Management,” concerns how business relies on online auctions to enhance efficiency

and reduce costs within a supply chain. The chapter focuses on the product sourcing

problems, and details existing bidding models and organizational dynamics that may

influence or be employed to improve bidding strategy.

Chapter 8, “Analytical Models for Integrating Supplier Selection and Inventory

Decisions,” focuses on analytical models for integrating supplier selection and inven￾tory decisions. The models involve such factors as long-term relationships, quality,

delivery performance, quantity discounts, replenishment quantity and timing, and

procurement and contractual costs.

Chapter 9, “Inventory Optimization of Small Business Supply Chains with

Stochastic Demand,” examines the supply chain in a small seasonal business and

inventory optimization with stochastic demand.

Section III: Optimization Models of Supply

Chain Problems

Chapter 10, “A Dynamic Programming Approach to the Stochastic Truckload Rout￾ing Problem,” addresses a continuously changing and challenging problem faced

by industry. In addition to traditional out-and-back routing, trucks are permit￾ted to extend their routes until restrictions are reached. This chapter develops and

presents the results of applying a dynamic programming solution approach to solve

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Introduction
xiii

an innovative triplet formulation to solve the stochastic truckload routing problem

with time windows.

Chapter 11, “Modeling Data Envelopment Analysis (DEA) Efficient Loca￾tion/Allocation Decisions II,” focuses on the multi-objective nature of the optimal

location of facilities. The results of these models have a significant impact on a

company’s operations and costs. This chapter extends the authors’ previous pioneer￾ing work of solving the location model and an efficiency model simultaneously by

permitting the outputs to be variable. The model is now nonlinear. The results of

applying the nonlinear model are presented.

Chapter 12, “Sourcing Models for End-of-Use Products in a Closed-Loop Sup￾ply Chain,” addresses how a green company places the closed-loop supply chain,

which is a combination of the traditional and reverse supply chains, as an integral

part of environmentally conscious manufacturing companies. Critical to these envi￾ronmentally conscious manufacturers is the identification of appropriate end-of-use

products from appropriate suppliers. To address these issues, a linear physical pro￾gramming model is developed to address the desirability selection of a product to be

reprocessed and a model that is a combination of analytic network process and goal

programming is developed to select suitable suppliers.

Chapter 13, “A Bi-Objective Supply Chain Scheduling,” focuses on the co￾ordination of manufacturing and supply with the production and distribution of

products as one of the key issues in supply chain management. Integrated and hier￾archical approaches are presented and compared to solve the bi-objective, maximize

customer service and minimize inventory holding cost, the problem of determining

a customer-driven supply chain (i.e., a coordinated schedule for the manufacture of

parts by each supplier), for the delivery of parts from each supplier to the producers,

and for the assignment of orders to planning periods at the producer. The results

from some computational examples are presented.

Chapter 14, “Applying Data Envelopment Analysis and Multiple Objective Data

Envelopment Analysis to Identify Successful Pharmaceutical Companies,” addresses

the development of superior forecasts as a key to a successful supply chain. The

chapter presents an innovative approach that incorporates multidimensional perfor￾mance variables into the regression forecasting model. Results from applying this

methodology to a real data set of fifty pharmaceutical companies are presented.

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