Multi-Objective Approach to Road Network Optimization: A Case of Freight Route in Nepal

Abstract

Transportation cost of freight associated with import and export imposes high level impact on consumer end in case of land locked countries like ours. Basically, the pre-haul and end-haul are prone to higher unit cost of transport characterised by uncertain situations during the haulage process. This result in additional cost to the consumer of the freight, for which they do not enjoy benefit. Capacity reliability is the function of driver’s preference to choose the path of travel and a multiplier set to adjust the reserve capacity of the network. Hence the increase in reserve capacity of the road increases the capacity reliability of the road network. Transportation authorities want the capacity reliability benefits derived from the improvement of road networks to be fairly distributed across the different parts of a country or a region because uneven welfare gains are not desired due to sustainable development objectives of public sectors. This is why decision maker (DM) gets interested in maximizing the reserve capacity of road network. Contrary to this, emphasis is placed by decision makers to minimize the construction cost for the upgrading inventory. These two objectives are not compatible among themselves and thus require multi-objective analysis for simultaneous optimization. Multi objective decision problems have been of increasing interest to management scientists, due to the realization that many problems, particularly those of strategic nature and more particularly those in public sector, most explicitly consider multiple criteria if they are to be resolved with truly good decisions. A non-dominated solution is a vector of solution for which none of the objective functions can be optimised without degrading some other objectives. In case if solutions are free from additional subjective preference, all non-dominated solutions are considered equally good. Multi-objective optimization problems are studied from different viewpoints in different researches and, there exist different solution philosophies while solving them. This work aims in finding a set of Pareto optimal (Non-dominated) solutions, and discuss the trade-offs between the different objectives, Transportation cost of freight associated with import and export imposes high level impact on consumer end in case of land locked countries like ours. Basically, the pre-haul and end-haul are prone to higher unit cost of transport characterised by uncertain situations during the haulage process. This result in additional cost to the consumer of the freight, for which they do not enjoy benefit. Capacity reliability is the function of driver’s preference to choose the path of travel and a multiplier set to adjust the reserve capacity of the network. Hence the increase in reserve capacity of the road increases the capacity reliability of the road network. Transportation authorities want the capacity reliability benefits derived from the improvement of road networks to be fairly distributed across the different parts of a country or a region because uneven welfare gains are not desired due to sustainable development objectives of public sectors. This is why decision maker (DM) gets interested in maximizing the reserve capacity of road network. Contrary to this, emphasis is placed by decision makers to minimize the construction cost for the upgrading inventory. These two objectives are not compatible among themselves and thus require multi-objective analysis for simultaneous optimization. Multi objective decision problems have been of increasing interest to management scientists, due to the realization that many problems, particularly those of strategic nature and more particularly those in public sector, most explicitly consider multiple criteria if they are to be resolved with truly good decisions. A non-dominated solution is a vector of solution for which none of the objective functions can be optimised without degrading some other objectives. In case if solutions are free from additional subjective preference, all non-dominated solutions are considered equally good. Multi-objective optimization problems are studied from different viewpoints in different researches and, there exist different solution philosophies while solving them. This work aims in finding a set of Pareto optimal (Non-dominated) solutions, and discuss the trade-offs between the different objectives, v and hence clarify the optimal solution strategy might meet the subjective preferences decision maker (DM). Here the non-dominated solutions are worked out to present multi-objective decision technique to suggest network optimization solutions at two contrasting objective functions. (i.e. maximizing reserve capacity of network, minimizing construction (upgrading) cost). and hence clarify the optimal solution strategy might meet the subjective preferences decision maker (DM). Here the non-dominated solutions are worked out to present multi-objective decision technique to suggest network optimization solutions at two contrasting objective functions. (i.e. maximizing reserve capacity of network, minimizing construction (upgrading) cost).