Research On Models And Algorithms For Purchase Planning With Outsourcing In Global Business Environment

Increasingly fierce competitions impel enterprises to strengthen the cooperation with supply chain partners and to collaboratively optimize their business activities for improving their competitiveness of products or services in the market. Purchase function is the main upriver activities of the supply chain, and is regarded as the key factor which affects the competitiveness of enterprises by many managers. Nevertheless, the existing enterprise management software only can achieve procurement information management, lacking in optimization features. Most enterprises made their procurement plans still in the light of experience, without considering the integration and optimization of purchasing plans in the supply chain level. Furthermore, to ensure the quality and services of the products and decrease cost, enterprises are more inclined to purchase from single supplier for the same sort of product or service. Outsourcing has become a common tactic for enterprises to cope with the volatile personality of demand today. Companies just retain core and high value-added business and subcontract other business. However, it is still relative shortage of the theoretical research on such topic currently.This dissertation is addressed on the problem of enterprise procurement plan with outsourcing in global business environment. And the research outspreads with Model Building, Algorithm Design and Algorithm Evaluation (Simulation Test).The main work and results is shown as follows.Firstly, the actual research background and motivation about such a topic is outlined and more comprehensive and in-depth survey on the research progress of procurement plan is made. It is indicated that integration procurement plan in supply chain level is the research trend in future.Secondly, a brief summarization is given about the basic lot sizing model of single item, dynamic programming algorithm, computational complexity theory, basic theory of genetic algorithm (GA). Moreover, a systemic summarization is given about the principle of Adaptive Genetic Algorithm, Hybrid Genetic Algorithm, constraint handling technique and the application of GA for optimization of lot sizing problems.Thirdly, the problem of dynamic single-item lot sizing with backlogging and outsourcing under non-decreasing inventory capacity constraint is studied. The properties of optimal solution about the problem is excavated and proved. A dynamic programming algorithm with complexity O(T~4) is developed to solve the global problem.Fourthly, the Expansion study of bounded inventory problem with outsourcing is made, which considering general time varying inventory holding capacity and backlogging. Based on the ideal of algorithm in Chapter 3, the dynamic programming algorithms with complexity and O(T~4logT) are developed according with outsourcing with stock-out and conservation. Fifthly, capacitated dynamic lot sizing problem with outsourcing and no-backlogging is addressed. In terms of special properties of lot sizing problem, a new heuristic algorithm is developed based on Genetic Algorithm. Compared with traditional genetic algorithm, the innovated algorithm has such predominant characteristics as the coding scheme, acquirement of feasible solutions, fitness calculation and the modification of the best solution.Finally, the expansion study of capacitated lot sizing problem with outsourcing is made, which considering general concave cost structure and backlogging. A new Adaptive Genetic Algorithm is developed to solve such a constrained optimization problem. A new adaptive penalty scheme is devised based on the feasibility of populations and the special information of individuals. Meanwhile, two types of probability adaptive schemes of genetic operators worthy of popularizing are innovated, and the problem of probability adaptive adjustment for genetic operator is discussed if infeasible individuals exist in populations.