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Research On Order Selection And Ordination In The Resource Constraints Of Enterprises

Posted on:2015-07-06Degree:MasterType:Thesis
Country:ChinaCandidate:L YangFull Text:PDF
GTID:2309330482960164Subject:Industrial Engineering
Abstract/Summary:PDF Full Text Request
With the development of information technology, companies have inventory from the traditional face-to-order production gradually transformed into production mode. Due to growing customer-driven force for production orders in profits for the enterprise, but also for the survival and development of enterprises has brought many challenges. To be able to dominate the competition in the market, more and more enterprises have begun to face-to-order production model as a corporate mainstream. In this environment, there are plans for implementation and management of orders is another problem facing enterprises. With customers, receiving a variety of orders, we can bring to the enterprise product revenue, profit; the other hand, due to individual enterprise production capacity, production orders to force the product would adversely affect business. Namely in the production process, inadequate materials, human waste and other unexpected losses tend to make business to break even or profit loss not arrived. Therefore, the decision makers, the face of a variety of orders, all reception and self-organization of production is sometimes not very sensible approach. How accordance with existing enterprise resource situation, without affecting the rest of the enterprise products and Master Production Scheduling (MPS) under the premise of the reach of rational selection and implementation of orders is an important business in the course of business must face problem of long-term business development of enterprises is essential.Firstly, the challenges of the modern mode of production enterprise applications in the process of receiving the order faced a brief analysis of the environment for the next multi-order companies receiving the order, the implementation of relevant research laid the theoretical foundation. Secondly, multi-order environment for business process design brief to receive orders, introduced the orders received from the finalization of the production of a series of processes. From the scope of the study has identified orders starting resources, delivery, profits and other indicators of orders in the production process to make a clear need to define the requirements of the corresponding mathematical model, using improved genetic algorithm research enterprise resource constrained Under the condition, how to select a larger number of orders, merit-based selection of the greatest profit organization of production orders from the line, ensure the realization of the objective function of maximum profit. While the first screening of many decision-making factors combine to make the order execution order of preliminary judging. For businesses avoid some of the orders of its own production, the proposed two methods for processing; was after one has been selected for the orders, the orders again eliminated choice. Under the conditions allow, introducing alternative models to analyze materials operations, the purpose of the order is selected again in the context of the protection of business reputation, so that production costs to a minimum. After two to be eliminated in order to select a third option, under the premise of guaranteed corporate earnings outside the Association to be adopted in the form for processing.Finally, the introduction of enterprise instance, according to the model to analyze data, to determine the final order of several options under way in order to implement and execute the target function. The manner conducive to filter out line with corporate profits and lower cost of higher orders, while reducing the risk of corporate compensation for the loss of customers, data analysis results demonstrate the reliability and feasibility of this model.
Keywords/Search Tags:Multiple Orders, Process Design, Order Selection, Order Execution, Numerical Example
PDF Full Text Request
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