Supply chain configuration objectives

Table 2.2 Methods for achieving alignment of supply chain configuration objectives...

Step 3— Experimental planning. In order to achieve supply chain configuration objective stated in Step 2, appropriate modeling and analysis methods are selected and experimental scenarios are defined. All parties involved also agree on acceptance criteria for modeling results and procedures for adjusting modeling results by human decision makers. 

In order to account for environmental factors, it is also important to consider a kind of capacity or resources used in supply chain processes. For instance, Chaabane et al. (2012) set capacity hmits for specific production technologies and the most appropriate production technology is used to minimize emissions associated with production as one of the supply chain configuration objectives. 

The conceptual modeling is performed to formally define the supply chain configuration problem in the case study. It is performed using the information modeling methods elaborated in Chap. 7. Figures 13.5 and 13.6 show the supply chain configuration objectives and the supply chain configuration concepts, respectively. 

Cohen and Roussel (2005) define strategic supply chain as a process to create a unique supply chain configuration that will drive the company s strategic objectives, and should consider five critical configuration components ... 

The supply chain configuration problem solving allows to define scope of the given supply chain system. The scope is defined along multiple dimensions, namely, horizontal extent, vertical extent, objectives and criteria, decisions made, and parameters. 

Definition of this supply chain configuration dimension includes specifying the number of units in each tier in the supply chain and identifying specific constraints and objectives (a) within a unit at high level and by functional areas at low level, and (b) between units at high level and across functional areas at low level. 

Decision-making objectives are chosen according to general strategic objectives. Certain quantitative criteria or metrics are associated with each identified objective. General managerial concerns related to the supply chain configuration problem are... 

Answering these questions leads to formulation of general supply chain configuration decision-making objectives. These objectives can be formulated on the basis of performance attributes identified in the SCOR model (Stewart 1997) as described in Table 2.1. 

The objectives of this state-of-the-art survey are to provide a comprehensive overview of the supply chain configuration problem, to identify main scientific and industrial focus areas, and to quantify the importance of different dimensions of the supply chain configuration problem. 

A data model is derived from the conceptual model to serve as the basis for data integration. The data model defines all objects, parameters, and costs relevant to the specific supply chain configuration problem. Values are assigned to these... 

The objective of this chapter is to describe the application of conceptual modeling techniques for supply chain configuration purposes. The general approach is to use well-known conceptual and information modeling techniques that would enable potential model-driven implementation of decision-modeling components. 

One of the main objectives of using conceptual modeling is providing a relatively easily tmderstandable representation of a problem. Several conceptual and information modeling techniques are usually applied to obtain a comprehensive representation of the problem. The choice of techniques and modeling concepts depends upon objectives of the information modeling application. In the framework of supply chain configuration, several objectives can be identified ... 

The following subsections define notation used to specify the generic supply chain configuration optimization model, and present the object function and constraints of this model. 

The objective function (Eq. 8.1) maximizes profit E determined as a difference between revenues 0 and total cost TC. As indicated in the previous chapter, profit maximization increasingly is considered as one of the main supply chain configuration performance measures. The total cost consists of multiple cost components... 

Multi-objective, stochastic, and nonlinear mathematical programming models are other models that find application in supply chain configuration. 

The generic formulation can be extended to multi-objective setting in various ways. Objectives associated with environmental issues, responsiveness, and reliability including customer service are considered most frequently. The generic supply chain configuration optimization model is extended to incorporate these additional objectives and the objective function (8.1) is reformulated as... 

Other multi-objective supply chain configuration models have been developed by Li and O Brien (1999), Sabri and Beamon (2000), Talluri and Baker (2002), Brandenburg (2015) and Das and Rao Posinasetti (2015) (see Chap. 3). 

Many of the stochastic programming models developed for supply chain configuration have demand as a stochastic parameter. Demand uncertainty usually is represented by multiple demand scenarios (Mirhassani et al. 2000 Tsiakis et al. 2001). In this case, a prototype objective function can be expressed as... 

Given that the simulation model is generally used to evaluate fixed supply chain configuration, it is developed on the basis of the object model containing objects, which are instances of classes defined in the class diagram of the generic supply chain unit. 

Section 11.2 discusses importance of the data driven approach in the overall supply chain configuration framework. Section 11.3 provides overview of the approach subsequently elaborated in Sects. 11.4 and 11.5. Application of the approach for multi-objective facility location is demonstrated in Sect. 11.6. 

The formulated optimization model defines relationships between the physical and information flows and takes into account QoS requirements for efficient information processing. Preliminary experimental results show that the information flows indeed affect selection of appropriate physical supply chain units. However, the QoS requirements have minor impact of the supply chain configuration decisions for the test supply chain analyzed in the chapter. An alternative approach to including QoS criteria directly in the objective model would be the specification of minimum quality requirements in the form of constraints. That would also alleviate the problem of selecting appropriate weights for multi-criteria optimization. The QoS characteristics also have impact on customer demand which could also be represented in the optimization model. 

Figure 14.5 offers graphical representation of the supply chain network. It shows that supply chain units are fixed and the configuration objective is to establish appropriate links among the units. The dashed line is used to represent the links in question. All suppliers involved in the supply chain configuration initiative are represented as a group and there are various options for connecting the customers with other supply chain units. 

Amin, S. H., and Zhang, G. An integrated model for closed-loop supply chain configuration and supplier selection Multi-objective approach. Expert Systems with Applications 39, no. 8 (2012) 6782-6791. 

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