A generic analytical target cascading optimization system for decentralized supply chain configuration over supply chain grid
ABSTRACT While centralized supply chain configuration (SCC) adopts an integrated decision model solved by an all-in-one decision method, decentralized SCC normally allows constituent enterprises to employ distributed decision models which are coordinated through a decomposition method to achieve an overall solution. Decentralized SCC paradigm could offer various contemporary advantages such as individual suppliers’ decision right protection and overall decision efficiency enhancement. This paper proposes an optimization system, atcPortal, to practically enable such a decentralized SCC process. Individual suppliers convert their local decision support systems into decision web services to form a distributed open-standard SCC service platform, called supply chain grid (SCG) in this paper. As a decomposition-based optimization method, analytical target cascading (ATC) is the mechanism for atcPortal to coordinate these web services through three phases of service searching, service-based ATC problem definition, and service-oriented ATC execution. atcPortal is a generic and extensible web portal in the sense that ATC accommodates a variety of decentralized SCC decision structures without confining the local decision models of individual enterprises. Finally, the usage of atcPortal is demonstrated through a typical decentralized SCC problem.
- [show abstract] [hide abstract]
ABSTRACT: This paper describes a methodology developed for designing an optimal configuration for a supply chain. A typical configuration for a supply chain consists of defining components of the system, assigning values to characteristics parameters of each component and setting operation policies for governing the interrelationships among these components. As such, each configuration will be defined by a set of values for quantitative parameters of the system as well as a set of policy and qualitative characteristics. Examples of quantitative variable include inventory levels and frequency of ordering where as location of distribution centres and mode of transportation between suppliers and the original equipment manufacturers (OEM) are the decision variables of policy and qualitative nature. The methodology presented here consists of a supply chain model builder coupled with two optimisation algorithms that automatically build a sequence of configurations that systematically move towards an optimum design. A combination of mixed integer programming and a genetic algorithm is used to determine simultaneously the values of quantitative as well as policy variables. The solution consists of strategic decisions regarding facility locations, stocking locations, supplier selection, production policies, production capacities, and transportation modes.International Journal of Production Research - INT J PROD RES. 01/2005; 43(11):2217-2236.
- [show abstract] [hide abstract]
ABSTRACT: This paper seeks to address the challenge of designing effective supply chain systems that integrate platform product decisions, manufacturing process decisions, and supply sourcing decisions. Specifically, this paper considers the specific scenario of optimizing the configuration of the supply chain system given commonality among platform products. The paper uses and extends the concept of Generic Bills of Materials (GBOM) of a product family as a unified framework for qualitatively capturing and representing the structure of its supply chain. This qualitative model is then enhanced by a mathematical model developed to quantify the relationships among various design decisions. Endeavoring to solve the mathematical model more efficiently, we propose an effective heuristic method using Genetic Algorithm (GA). Although GA generally does not guarantee the optimal solution, the best heuristic solutions obtained in this study are consistent with the optimal solutions obtained using Dynamic Programming. The resulting mathematical model and solution algorithm are then used to investigate the mutual impact between the design decisions of platform products and of processes in the supply chain through sensitivity analyses. Several useful managerial insights are generated and discussed.Journal of Operations Management. 01/2005;
Conference Proceeding: Decentralization of Process Nets with Centralized Control.[show abstract] [hide abstract]
ABSTRACT: The behavior of a net of interconnected, communicating processes is described in terms of the joint actions in which the processes can participate. A distinction is made between centralized and decentralized action systems. In the former, a central agent with complete information about the state of the system controls the execution of the actions; in the latter no such agent is needed. Properties of joint action systems are expressed in temporal logic. Centralized action systems allow for simple description of system behavior. Decentralized (two-process) action systems again can be mechanically compiled into a collection of CSP processes. A method for transforming centralized action systems into decentralized ones is described. The correctness of this method is proved, and its use is illustrated by deriving a process net that distributedly sorts successive lists of integers.01/1983 · 0.63 Impact Factor