A global routing problem is formulated as a multi-commodity network flow problem. The formulation gives no restriction over the shape of a routing pattern and makes it possible to obtain the optimal solution by using a mathematical programming method. Moreover, it can be naturally extended to the problem even optimizing routing length objectives for net delay and clock skew perfomances by using the goal programming method. An approximation algorithm solving the multi-commodity network flow problem is proposed by adding a merge step of wires whose source-sink pairs are exactly the same and a step restricting an area for searching routes. Experimental results show that this global routing algorithm connected with a line-search detailed router can generate a complete routing for interblock routing problems with more than 2400 wires in two industrial chips. The total amount of procassing time for both problems is about 90 minutes on a mainframe computer.

In this paper, we propose an approach to solve the power control issue in a DS-CDMA cellular system using genetic algorithms (GAs). The transmitter power control developed in this paper has been proven to be efficient to control co-channel interference, to increase bandwidth utilization and to balance the comprehensive services that are sharing among all the mobiles with attaining a common signal-to-interference ratio(SIR). Most of the previous studies have assumed that the transmitter power level is controlled in a constant domain under the assumption of uniform distribution of users in the coverage area or in a continuous domain. In this paper, the optimal centralized power control (CPC) vector is characterized and its optimal solution for CPC is presented using GAs in a large-scale DS-CDMA cellular system under the realistic context that means random allocation of active users in the entire coverage area. Emphasis is put on the balance of services and convergence rate by using GAs.