以印刷电路板的制造过程为背景，总结了柔性制造/装配系统各种柔性的定义。基于柔性制造系统的柔性既取决于设备本身的性能，也取决于对驱动柔性制造/装配系统自动化运行的指令的认识，提出了柔性与大M制造各个过程的决策问题的关系框架。还提出一种新的部分柔性制造系统生产能力规划与生产线设计的模型，并分析探讨了决策问题的求解方法。

A model of scenario-based line capacity expansion problem for PWB (Printed Wiring Board) assembly systems at the aggregate level is developed. The model synthesizes BOM (Bill Of Material) of product families and machine operation flexibility, thus it is an attempt of integrating strategic capacity planning, aggregate production planning and MPS (Master Production Scheduling), which is an important research topic of production management. Since the resulting model is a large-scale two-stage stochastic mixed integer programming problem, it can not be solved with standard code. An approximate solution procedure is developed, which first reduces the searching space of capacity expansion decision variables to rough addition sets by heuristics, then the rough addition sets are searched through adaptive genetic algorithms. Numerical experiments are presented to show the financial benefit of the model and the feasibility of our approach.

In a multi-product, flexible manufacturing environment, line capacity of printed wiring board (PWB) assembly systems may need to be adjusted at the beginning of each aggregate planning period because of demand fluctuation over multiple periods. A model of production planning and equipment changeover scheduling at the aggregate level is developed. In the described model, three kinds of equipment changeover methods, i.e. adding machine, removing machine and transferring machine, are involved. Because the model is a large-scale integer programming problem, it cannot be solved directly. A solution approach is developed, which first solves a recursive linear programming problem to obtain a rough set of machines to be added and a rough set of machines to be removed for each machine line in each period, then applies a branch and bound heuristic to the rough sets to obtain near-optimal solutions to the equipment changeover scheduling problem. Computational studies show the financial benefit both on capital cost and equipment changeover costs.

Cooperation is an approach of improving competitive advantages of a supply chain. A two-echelon supply chain consisting of a manufacturer and a retailer for a single-period product is studied, and retail-market demand uncertainty is described by coefficient of variation. We develop a cooperation mechanism to address the cooperation and its implementation between the manufacturer and the retailer, two market situations are considered: (i) the wholesale price and the order quantity are decision variables, (ii) the wholesale and the retail prices as well as the order quantity are decision variables. In both market situations, our research shows that: (1) the cooperation mechanism can improve the overall channel profits and the supply chain members' allocated profits, (2) the described cooperation is conditional on retail-market demand uncertainty: it can be implemented if, and only if, the fluctuation of retail-market demand is relatively small and coefficient of variation of retail-market demand does not exceed an upper bound. Impacts of retailmarket demand uncertainty on wholesale price, order quantity and/or retail price have also been investigated through analytical and numerical analyses. Although our research is based on the assumption that the manufacturer dominates the supply chain in the non-cooperative situation, which is not the case for most retailer-driven supply chains, this research is still significant on providing guidelines for practitioners in current China mid-level car market that is similar to situations described in the paper.

This paper chooses a Data Envelopment Analysis (DEA) model for different areas to identify the difference in solving the industrial pollution problem by comparing their levels of efficiency. Generally, the industrial pollution problem calls for within-area treatments, although these affect areas beyond their limits. Following this fact, a Maximal Efficiency Sum (MES) DEA Model is used to estimate the anti-industrial pollution efficiency of different cities in Anhui province of China.

Quadratic knapsack problem (QKP) has a central role in integer and combinatorial optimization, while efficient algorithms to general QKPs are currently very limited. We present an approximate dynamic programming (ADP) approach for solving convex QKPs where variables may take any integer value and all coefficients are real numbers. We approximate the function value using (a) continuous quadratic programming relaxation (CQPR), and (b) the integral parts of the solutions to CQPR.We propose a new heuristic which adaptively fixes the variables according to the solution of CQPR.We report computational results for QKPs with up to 200 integer variables. Our numerical results illustrate that the new heuristic produces high-quality solutions to large-scale QKPs fast and robustly.

In a multi-product, flexible manufacturing environment, line capacity of printed wiring board (PWB) assembly systems may need to be designed at the beginning of each aggregate planning period because of demand #uctuation over multiple periods. A model of line capacity design problem and production planning at the aggregate level is developed, in which production and subcontracting are assumed to be two options for a firm to meet market demand. The model presented is a large-scale integer programming roblem, it cannot be solved by using standard-or mixed-integer programming codes. Under the ssumption that each machine line is dedicated to produce one product family, the model can be decomposed as a relatively small subproblem, and each subproblem has good properties by which the subproblems can be further simplified and decomposed over multiple planning periods. As the result, the original large-scale two-stage integer programming problem can be approximately solved by solving a series of small-scale mixed-integer programming, which can be implemented on a workstation or a PC. Computational studies show that the solution method is developed which gives near-optimal solutions with much less computational errort.

As a result of the fierceness of business competition, companies, to remain competitive, have to charm their customers by anticipating their needs and being able to rapidly develop exciting new products for them. To overcome this challenge, technology forecasting is considered as a pow-erful tool in today's business environment, while there are as many success stories as there are fail-ures, a good application of this method will give a good result. A methodology of integration of patterns or lines of technology evolution in TRIZ parlance is presented, which is also known as TRIZ technology forecasting, as input to the QFD process to design a new product. For this purpose, TRIZ technology forecasting, one of the TRIZ major tools, is discussed and some benefits compared to the traditional forecasting techniques are highlighted. Then a methodology to integrate TRIZ technology forecasting and QFD process is highlighted.

合作是提高供应链竞争力的途径，也是增强供应链企业抵御经营风险的重要手段。研究了由一个生产商和一个零售商组成的两层供应链，用变异系数（需求的均方差与其均值之比）描述单周期产品市场需求的不确定性。研究发现在一定的市场需求不确定性条件下，生产商与零售商才存在合作博弃均衡;通过市场需求不确定性的变化对合作均衡与合作效果影响的数值分析，及其与非合作情形的对比，结果说明在给定的零售价格水平下，合作具有改善供应链企业应对市场需求不确定性变化和规避经营风险的能力。