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.

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.

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.