Disclosure is a multi-objective semiconductor product capacity planning system and method thereof. The system comprises a data input module, a capacity planning module and a computing module. The machine information of the production stations, the product information and the order information are input by the data input module. According to the demand quantity of order, capacity information and product information, the capacity planning module plans a capacity allocation to determine the satisfied quantity of orders. The capacity allocation information is used to form a gene combination by chromosome encoding method. The computing module calculates the gene combination several times to generate numerous candidate solutions by a multi-objective genetic algorithm. The numerous candidate solutions sorts out and generates a new gene combination, and repeats the calculation to form candidate solution set until stop condition is satisfied. The candidate solution set is transformed into numerous suggestive plans as options.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A multi-objective semiconductor product capacity planning system, comprising: a data input module, accepting inputs of machine information, product information and order information, the machine information defining a plurality of production stations and a capacity limit of the plurality of production stations, the product information defining a plurality of product categories and a production cost of the plurality of product categories, the order information defining a demand quantity of order for a plurality of customer orders and a product price; a capacity planning module, receiving input data from the data input module, coordinating the demand quantity of order with the machine information and the product information to plan a satisfied number of order to satisfy the capacity limit, determining the satisfied number of order by a capacity allocation proportion of order to decide a capacity utilization rate of each of the orders and a satisfied priority of order to arrange a production sequence of each of the orders, combining the capacity allocation proportion of order and the satisfied priority of order as a resource allocation and transforming the resource allocation into a gene combination by a chromosome encoding method; and a computing module, receiving the gene combination from the capacity planning module, calculating the gene combination several times to generate a plurality of new candidate solutions by using a multi-objective genetic algorithm, sorting the plurality of new candidate solutions by using a plurality of planning objectives as evaluation criteria to generate a new gene combination, and repeating the calculation to form a candidate solution set until a stop condition is satisfied, transforming the candidate solution set into a plurality of suggestive plans and selecting one of the plurality of suggestive plans to arrange the production stations for manufacturing the product categories. 2. The multi-objective semiconductor product capacity planning system of claim 1, wherein, the plurality of planning objectives of the computing module comprise a financial index related to a revenue, a profit or a gross margin, or a production index related to a production quantity or a capacity utilization. 3. The multi-objective semiconductor product capacity planning system of claim 1, wherein, the plurality of planning objectives are a revenue maximization, a profit maximization and a gross margin maximization. 4. The multi-objective semiconductor product capacity planning system of claim 1, wherein, the computing module sorts out and generates the new gene combination by a Pareto front method. 5. The multi-objective semiconductor product capacity planning system of claim 1, further comprising a report module for presenting the plurality of suggestive plans. 6. A multi-objective semiconductor product capacity planning method, applicable to a multi-objective semiconductor product capacity planning system comprising a data input module, a capacity planning module and a computing module, the method comprising: receiving machine information from a production machine of each production stations, and product information and order information input by the data input module; planning a satisfied number of order by the capacity planning module, deciding a capacity utilization rate of each of the orders as a capacity allocation proportion of order and arranging a production sequence of each of the orders as a satisfied priority of order, combining the capacity allocation proportion of order and the satisfied priority of order as a resource allocation to form a gene combination by a chromosome encoding method; using a multi-objective genetic algorithm for the evolution of the gene combination for generating a plurality of new candidate solutions by the computing module; using a plurality of planning objectives as the evaluation criteria to sort the plurality of new candidate solutions for generating a new gene combination by the computing module; repeating the calculation to form a candidate solution set by the computing module until a stop condition is satisfied; and transforming the candidate solution set into a plurality of suggestive plans and selecting one of the plurality of suggestive plans to arrange the production stations for manufacturing a product. 7. The method of claim 6, further comprising following step: using a revenue, a profit, a gross margin, a production quantity or a capacity utilization as an index of the plurality of planning objectives. 8. The method of claim 6, further comprising following step: serving a revenue maximization, a profit maximization and a gross margin maximization as the plurality of planning objectives through the planning module. 9. The method of claim 6, further comprising following step: sorting by a Pareto front method and generating the new gene combination. 10. The method of claim 6, further comprising following step: presenting the plurality of suggestive plans by using a report module.