Solving Minimum Cost Multi-Commodity Network Flow Problem Using Lexicographic Goal Programming Approach

In an urban transport system, a dysfunction often occurred as demand for transportation infrastructure exceeds available supply. the result includes traffic congestion, higher travel time and cost, higher emission of harmful gases and general reduction in quality of life. in this research, an attempt was made to minimize travel time on three urban road segments using lexicographic goal programming. the positive and negative deviations from the goals were minimized. a minimum cost multi-commodity network flow problem with multiple objectives was successfully modelled using lindo 6.1. the modelling technique provided a solution that effectively minimized travel time by 50%.