In this paper,the authors consider some inverse problems on network,such as the inverse transport problems with gains(IGTP) and the inverse linear fractional minimum cost flow problem(IFFP).Firstly,the authors give th...In this paper,the authors consider some inverse problems on network,such as the inverse transport problems with gains(IGTP) and the inverse linear fractional minimum cost flow problem(IFFP).Firstly,the authors give the mathematics model of(IGTP) and an efficient method of solving it under l_1 norm;Secondly,taking advantage of the optimality conditions,the authors consider the(IFFP) and give a simple method of solving it.Finally,an numerical example test is also developed.展开更多
Transportation problem on network needs to determine the freight quantity and the transportation route between supply point and demand point. Therefore, taken the uncertainty of freight supply and demand into account,...Transportation problem on network needs to determine the freight quantity and the transportation route between supply point and demand point. Therefore, taken the uncertainty of freight supply and demand into account, a collaborative optimization model is formulated with transportation capacity constraint. In addition, a two-stage genetic algorithm （GA） is put forward. Herein, the first stage of this GA is adopted a priority-based encoding method for determining the supply and demand relationship between different points. Then supply and demand relationship which the supply and the demand are both greater than zero is a minimum cost flow （MCF） problem on network in the second stage. Aim at the purpose to solve MCF problem, a GA is employed. Moreover, this algorithm is suitable for balance and unbalance transportation on directed network or undirected network. At last, the model and algorithm are verified to be efficient by a numerical example.展开更多
基金supported by Shanghai leading academic discipline project under Grant No.S30501Shandong province leading academic discipline project under Grant No.ZR2010AM033
文摘In this paper,the authors consider some inverse problems on network,such as the inverse transport problems with gains(IGTP) and the inverse linear fractional minimum cost flow problem(IFFP).Firstly,the authors give the mathematics model of(IGTP) and an efficient method of solving it under l_1 norm;Secondly,taking advantage of the optimality conditions,the authors consider the(IFFP) and give a simple method of solving it.Finally,an numerical example test is also developed.
基金This project is supported in part by Natural Science Foundation of Gansu Province （0710RJZA048） National Natural Science Foundation of China（60870008）
文摘Transportation problem on network needs to determine the freight quantity and the transportation route between supply point and demand point. Therefore, taken the uncertainty of freight supply and demand into account, a collaborative optimization model is formulated with transportation capacity constraint. In addition, a two-stage genetic algorithm （GA） is put forward. Herein, the first stage of this GA is adopted a priority-based encoding method for determining the supply and demand relationship between different points. Then supply and demand relationship which the supply and the demand are both greater than zero is a minimum cost flow （MCF） problem on network in the second stage. Aim at the purpose to solve MCF problem, a GA is employed. Moreover, this algorithm is suitable for balance and unbalance transportation on directed network or undirected network. At last, the model and algorithm are verified to be efficient by a numerical example.
