Abstract
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%.
Highlights
Transportation networks are complex systems, and come in a variety of forms, such as road, rail, air, and waterway networks
Demand for transportation is represented by the users of the transportation system while the supply is represented by the underlying network topology and the ability to meet the demand given the cost characteristics (Sheffi, 1985)
An equilibrium occurs when the number of trips between an origin and destination equals the travel demand given by the market price, typically, represented by the travel time for the trips (Nagurney and Dong, 2004)
Summary
Transportation networks are complex systems, and come in a variety of forms, such as road, rail, air, and waterway networks. In urban conurbation of developing nations, such as Lagos, several transportation related problems exists, including inadequate road capacity to meet swelling demand and faulty network topology (intersections/junctions). They in no small way affect travel time. In Lexicographic Goal Programming, objective functions are ordered according to their importance This implies that goals of higher priority must be met before those of lower priority are considered. - constant for representing the preemptive priority of deviational variables and ; j - the index set of goals placed in the 1+ith priority level; n - total number of attributes separated in P priority levels;
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