汪定伟
计算机集成制造，ERP/MRP/JIT，生产计划与调度，建模与优化，软计算方法等
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 姓名：汪定伟
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学术头衔：
博士生导师
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学科领域：
控制理论
 研究兴趣：计算机集成制造，ERP/MRP/JIT，生产计划与调度，建模与优化，软计算方法等
汪定伟，男，汉族，中共党员。１９８２年在东北大学获学士学位，１９８４年在华中理工大学获硕士学位后在东北大学系统工程任教至今。其间，于１９９３年９月在东北大学控制理论与应用专业获博士学位，并先后在美国北卡罗来纳州立大学作访问学者、博士后和访问教授。现任东北大学系统工程研究所所长，教授，博士指导教师。主要研究方向包括计算机集成制造，ERP/MRP/JIT,生产计划与调度，建模与优化，软计算方法等。研究成果获国家教育部科技进步(甲类)二等奖两项，冶金行业科技进步二等奖一项。出版著译6部，在国内外杂志会议发表论文240余篇，包括ＩＥＥＥ长文5篇。论文被ＳＣＩ收录48篇，ＥＩ收录62篇，并被广大国内外同行引用，在国内外有很大的学术影响。 2002年，评为辽宁省优秀专家 2002年，评为沈阳市劳动模范 2001年，评为沈阳市优秀专家 2000年，评为沈阳市优秀教师主要社会兼职有：国家自然科学基金委员会管理科学部专家组成员中国自动化学会系统工程专业委员会委员冶金自动化学会控制理论应用学术委员会委员辽宁省自动化学会理事国际杂志《Computer and Operations Research》编委（2000－2002）国际杂志《Fuzzy Optimization and Decision Making》编委《系统工程学报》编委《管理科学学报》编委《控制与决策》编委《东北大学学报》编委

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成果数
10
汪定伟， Shengxiang Yang and Dingwei Wang
，0001，（）：
1年11月30日
This paper presents a constraint satisfaction adaptive neural network, together with several heuristics, to solve the generalized jobshop scheduling problem, one of NPcomplete constraint satisfaction problems. The proposed neural network can be easily constructed and can adaptively adjust its weights of connections and biases of units based on the sequence and resource constraints of the jobshop scheduling problem during its processing. Several heuristics that can be combined with the neural network are also presented. In the combined approaches, the neural network is used to obtain feasible solutions, the heuristic algorithms are used to improve the performance of the neural network and the quality of the obtained solutions. Simulations have shown that the proposed neural network and its combined approaches are efficient with respect to the quality of solutions and the solving speed.
Adaptive neural network,， constraint satisfaction,， generalized jobshop scheduling problem,， heuristic.，

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【期刊论文】Soft Computing for Multicustomer DueDate Bargaining
汪定伟， Dingwei Wang， ShuCherng Fang， and Henry L. W. Nuttle
，0001，（）：
1年11月30日
The duedate bargainer is a useful tool to support negotiation on due dates between a manufacturer and its customers. To improve the computational performance of an earlier version of the duedate bargainer, we present a new soft computing approach. It uses a genetic algorithm to find the best priority sequence of customer orders for resource allocation and fuzzy logic operations to allocate the resources and determine the ordercompletion times, following the priority sequence of orders. To extend the duedate bargainer to accommodate bargaining with several customers at the same time, we propose a method to distribute the total penalty using marginal penalties for the individual bargainers. A demonstration software package implementing the improved duedate bargainer has been developed. It is targeted at apparel manufacturing enterprises. Experiments using realistic resource data and randomly generated orders have achieved satisfactory results.
Duedate assignment,， fuzzy optimization,， genetic algorithms,， JIT,， MRPII,， production planning,， soft computing.，

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【期刊论文】A Fuzzy DueDate Bargainer for the MaketoOrder Manufacturing Systems
汪定伟， Dingwei Wang， ShuCherng Fang， and Thom J. Hodgson
，0001，（）：
1年11月30日
For a maketoorder manufacturing system, the uncertainty and flexibility of the due dates required by customers and the production capacity owned by the manufacturer can be modeled in a fuzzy environment. In this paper, a combined duedate assignment and production planning methodology for the maketoorder manufacturing systems is developed. The fuzzy approach determines the optimal due dates for the manufacturer based upon a "roughcut" resource balance, while a customer can request earlier due dates by paying a higher price to cover the extra manufacturing cost incurred. The resulting fuzzy duedate bargainer is exercised using manufacturing resource planning (MRPII) data from a furniture manufacturing company. Experimental results indicate its potential as a useful tool for real applications.
Branchandbound,， duedate assignment,， fuzzy optimization,， justintime (， JIT)， ,， MRPII,， production planning.，

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【期刊论文】A GeneticsBased Approach for Aggregated Production Planning in A Fuzzy Environment
汪定伟， Dingwei Wang and ShuCherng Fang
，0001，（）：
1年11月30日
Due to the nondeterministic nature of the business environment of a manufacturing enterprise, it is more appropriate to describe the aggregated production planning by using a fuzzy mathematical programming model. In this paper, a geneticsbased inexact approach is proposed to imitate the human decision procedure for production planning. Instead of locating one exact optimal solution, the proposed approach finds a family of inexact solutions within an acceptable level by adopting a mutation operator to move along a weighted gradient direction. Then, a decision maker can select a preferred solution by examining a convex combination of the solutions in the family via the humancomputer interaction. Our computational experiments illustrate how the enterprise managers can be more satisfied by this new approach than others.

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【期刊论文】A humancomputer interactive approach based on activitysection analysis for BPR
汪定伟， DINGWEI WANG， ZHIWEN TANG， W. H. IP and RICHARD Y. K. FUNG
PRODUCTION PLANNING & CONTROL, 2000, VOL. 11, NO.8, 789796，0001，（）：
1年11月30日
In any business process reengineering (BPR) project, a thorough understanding of various tasks and activities of the organization is required. Very often this idea is captured using a simple flow chart or static representation diagram. The weakness here is that the process design complexity is not adequately represented by the use of flow charts, and this allows for limited humancomputer interaction during the process design and analysis. In this paper, we propose an enhanced flow chart approach; the concept of activitysection flow chart to support BPR, which is a combination of the existing activity flow chart and section flow chart. Using this approach, a humancomputer interactive model for BPR is developed. This model can identify the unreasonable activity loops and excessive business rounds between sections by the adjacent and reachable matrices. Via the humancomputer interaction, the process can be revised by human experience. This approach provides an e
BPR,， activity flow chart,， reachable matrix,， structure modelling,， humancomputer interaction

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汪定伟， Dingwei Wang， K. L. Yung， and W. H. Ip
，0001，（）：
1年11月30日
In this paper, we present an investigation of how partner selection problems may be optimized by the use of a precedence network of subprojects. At the start, the problem is described by a model with the subscripttype of variables and nonanalytical objective function. It cannot be solved by general mathematical programming methods. By using the fuzzy rule quantification method, a fuzzy logic based decision making approach for the project scheduling is proposed. We then develop a fuzzy decision embedded heuristic genetic algorithm (GA/FD) to find the solution for partner selection. The approach was demonstrated by the use of an experimental example drawn from a coal fire power station construction project. The results show us that the suggested approach is possible to quickly achieve optimal solution for large size problems.
Agile manufacturing,， fuzzy logic,， genetic algorithm (， GA)， ,， partner selection,， project management,， soft computing,， virtual enterprise.，

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【期刊论文】An inexact approach for linear programming problems with fuzzy objective and resources
汪定伟， Dingwei Wang*
Fuzzy Sets and Systems 89(1997)6168，0001，（）：
1年11月30日
An inexact approach is proposed to solve objective/resource type of fuzzy linear programming problems. Instead of finding an exact optimal solution, this approach uses a recommended genetic algorithm with mutation along the weighted gradient direction to find a family of inexact solutions with acceptable membership degree. Then, by means of the humancomputer interaction, the solution preferred by the decisionmaker can be achieved by a convex combination of the solutions selected from the family. The numerical analysis has shown that the more satisfactory results can be achieved by this new approach.
Fuzzy sets of solutions， Mathematical programming， Decision making， Genetic algorithms， Optimization， Humancomputer interaction

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汪定伟， DINGWEI WANG， S.C. FANG
Computer8 Math. Applic. Vol. 31, No.8, pp. 95106, 1996，0001，（）：
1年11月30日
To closely describe the earliness/tardiness production planning problems in the JIT environment, a nonlinear semiinfinite programming model is proposed. Due to the issues of nonconvexivity and having infinitely many constraints, instead of applying traditional optimization approaches, a specially designed genetic algorithm with mutation along the negative gradient direction is developed. The proposed algorithm is a combination of the steepest descent method with the stochastic sampling algorithm. Some numerical results are included to show its potential for industrial applications.
Production planning,， Earliness/， tardiness schedule,， Genetic algorithm,， Semiinfinite programming.，

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【期刊论文】Scheduling grouped jobs on single machine with genetic algorithm
汪定伟， Dingwei Wang a， *， Mitsuo Gen b， Runwei Cheng b
Computers & Industrial Engineering 36(1999)309324，0001，（）：
1年11月30日
Production scheduling of grouped jobs has been an active research area since GT (Group Technology) was widely applied in practical manufacturing systems. To minimize the total flowtime of grouped jobs on a single machine, we combine jobs into fundamental runs based upon the necessary condition of the optimal solution. It is proved that the optimal solution is a combination of fundamental runs. A genetic algorithm is designed based on studies on the combinatorial rules of fundamental runs. The numerical results show that the computational performance of the algorithm depends on the number of `fundamental' runs, not on the number of jobs. In general, the number of fundamental runs is far less than the number of jobs. Therefore, the algorithm has potential for practical application in large scale production systems.

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