In this paper, we consider the set partitioning problem with matroid constraint, which is a generation of the k-partitioning problem. The objective is to minimize the weight of the heaviest subset. We present an approximation algorithm, which consists of two sub-algorithms-the modified Edmonds' matroid partitioning algorithm and the exchange algorithm, for the problem. An estimation of the worst ratio for the algorithm is given.
In this paper, the k-partitioning problem with partition matroid constraint is considered. LPT algorithm is modified to fit the problem and its worst-ease performance is analyzed. The lower bounds of optimal solution for the min-max problem are given.
Manufacturing network flow （MNF） is a generalized network model that overcomes the limitation of an ordinary network flow in modeling more complicated manufacturing scenarios, in particular the synthesis of different materials into one product and/or the distilling of one type of material into many different products. Though a network simplex method for solving a simplified version of MNF has been outlined in the literature, more research work is still needed to give a complete answer whether some classical duality and optimality results of the classical network flow problem can be extended in MNF. In this paper, we propose an algorithmic method for obtaining an initial basic feasible solution to start the existing network simplex algorithm, and present a network-based approach to checking the dual feasibility conditions. These results are an extension of those of the ordinary network flow problem.
