The framework and organization of this dissertation is shown in Figure 1.2.
Figure 1.2 depicts the content and models of each part of this dissertation. Chapter 1 illustrates the overview of this dissertation in terms of motivations and background, objectives, spectrum and approach of the framework. Chapter 2 reviews literature in the relevant topics and distinguishes the study from past studies, in which the contributions of each part of this dissertation are also emphasized. Chapter 3 presents a basic supply chain network design model, where the decisions on plant capacity and production amount of the manufacturing plants are emphasized. In the model, how the demand from customers in different locations, investment conditions and scale economies influence the capacity and production allocation among the manufacturing plants are analyzed. The supply chain network design model is formulated as a MIP model, which attempts to minimize the average total cost per unit-product subject to constraints such as satisfying customer demand in various geographic regions, relationships between supply flows and demand flows within the physical configuration and the production limitation of different size plants.
Chapter 4 evaluates the performance of the results from Chapter 3 on condition that abnormal demand fluctuations occur. In accordance with the unreliable situations, the adjustment strategy is proposed, where the pro and con of the adjustment are analyzed by analytical approaches. Two mathematical programming models with respect to demand expansion and demand shrinkage are further developed to determine the optimal adjustment decisions, regarding production reallocations, manufacturing plants-customers reassignments and outsourcing firms selections, etc. The judgment on performing an adjustment or do nothing is also investigated by comparing between the results if no adjustments are made and if adjustment are made during the duration of
an abnormal state.
Chapter 5 focuses on investigating supply chain network design problems when incorporating inbound and outbound dispatching decisions by considering production and shipping economies. A MIP model is also formulated to determine not only decisions as Chapter 3 but also to determine the optimal shipping size and frequency between supply and demand by minimizing the sum of the average inbound, production and outbound costs. In the model, the impacts on the optimal shipping frequency and shipment size and resulting costs because of the geographical combinations of suppliers and manufacturing plants and the total monthly procurement/product amount between them are analyzed. Moreover, the impacts of the key-component price by suppliers, which are located at different distance to the manufacturing plants, on the optimal supplier selection are also investigated.
Chapters 6 and 7 focuses on the logistics issues with regard to delivery service strategies in the supply chain with time-dependent demand. Time and spatial dependent customer demand are first analyzed in Chapter 6. Then, this study formulates manufacturer cost functions as they cope with time and spatial dependent customer demand, where the impacts of production and transportation cost economies on total costs are also incorporated. The customer choice probability are formulated to capture the influences of delay in receiving products from the manufacturer, depended on the spatial distance and service cycles, and the product price charged by the manufacturer. The customer demand model is further estimated by aggregating time and spatial dependent customer demand. Combining with the customer demand function and the manufacturer cost function, a mathematical programming model is formulated for determining an optimal delivery service strategy in terms of the number and duration of service cycles for various customers and the assignments of the
manufacturing plants in serving these customers by taking demand-supply interaction into account. The demand-supply interactions on the delivery service strategy programming are discussed. Moreover, the impacts of demand-supply interaction on the determinations of capacity and production of the manufacturing plants are also investigated.
Turning the focus from the customers (retailers) into end users, Chapter 7 designs a consumer choice probability model for choosing between Internet and conventional shopping modes, by taking various factors into account. These factors include differences in consumer socioeconomic characteristics, temporal variations in ordering time of consumer goods, and spatial variations in consumer locations and competitions between Internet stores and retail stores in urban and non-urban areas. Moreover, total customer demand for Internet store goods during different service cycles are estimated by multiplying time-dependent consumer demand and the expected probability of selecting Internet shopping. Regarding the supply side, the logistics cost function, including transportation cost and inventory cost, is developed to analyze how consumer demand for goods influences logistics cost for Internet store operators. Combining with consumer choice model and operator logistic cost function, the optimal delivery service strategy problem is formulated as a mathematical programming model by maximizing operator profit during the study period.
Production scale
Supply chian network design model when incorporating
Supply chain network design problems
Time-dependnet for Internet shopping with
time-dependent demand
Chapter 5Chapter 7
Introduction Chapter 1 Literature review Chapter 2
Conclusions Chapter 8
Figure 1.2 The framework of the dissertation
Figure 1.3 depicts the research processes and the steps can be expressed in detail as follows.
1. Define the research problems
According to the motivation and backgrounds, the research problems, issues, scope and objectives are first identified.
2. Literature review
To better understand the problems, this dissertation comprehensively reviews the existing literature in the relevant topics so as to understand the important factors when designing the supply chain network and when determining the optimal delivery service strategy, and to illuminate the contributions of this research.
3. Customer demand and manufacturer cost analysis
Next, customer demand characteristics are investigated. From long-term planning perspectives, events as well as important factors affecting customer demand are identified. Meanwhile, the derivative costs in serving customers are also investigated.
These demand and supply analysis are the fundamentals of the model constructions.
4. Supply chain network design model
Based on the analysis in Step 3, the essential cost functions can be formulated.
Employing the mixed integer programming models and related analytical techniques, this dissertation formulates a series of supply chain network design models, in which various topics are emphasized.
4.1 Reliability evaluation method
This dissertation further discusses how the performance of the manufacturing plants will be influenced by demand fluctuations by means of investigating the relationships between customer demand and production allocation. After some assumptions are made, this dissertation further formulates reliability evaluation method so as to evaluate the performance of the manufacturing plants on condition that an abnormal event occurs.
4.2 Adjustment method
In view of how economies of scale and customer demand affect manufacturer costs, various adjustment methods in accordance with different fluctuant demand are proposed.
Furthermore, the advantage and disadvantage of the proposed adjustment methods are also discussed by constructing analytical models.
4.3 Supply chain network adjustment model
The mathematical programming model is employed herein to determine the optimal adjustment decisions. And the judgment of do-nothing and adjustment is also done by comparing the objective functions under condition that if and if not an adjustment is performed.
5. Demand-supply interaction
The other major part of this dissertation aims at designing the optimal delivery service strategy under different pattern of fluctuant demand, i.e. time-dependent customer demand. Based on the analysis in Step 3, how the customer demand is affected by the service provided and the interrelationship between customer demand and manufacturer costs can be analyzed and developed by analytical approaches.
6. Mathematical programming model for the optimal delivery service strategy
The demand-supply interactions on the delivery service strategy programming are analyzed, by integrating supply and demand models and using an algorithm to solve the problem.
7. Case studies and sensitivity analysis
Case studies and sensitivity analysis are provided in each parts of this dissertation to illustrate the application of the models and to demonstrate the proposed models’
effectiveness.
8. Conclusions and suggestions
Finally, the summary, conclusions and the future studies of this dissertation are presented.
Define the research problems
Literature review
Customer demand and manufacturer cost analysis
Supply chain network desgin model Objectives
Contraints
Reliability evaluation method
Adjustment methods
Benefits and costs analysis
Supply chain network adjustment model Objectives
Constraints
Mathematical programming model for the optimal delivery service strategy Objectives
Constraints
Demand-supply interaction analysis
Case studies and sensitivity analysis
Conclusions and suggestions
Figure 1.3 The research process flowchart