Application of Large Neighborhood Search method in solving a dynamic dial-a-ride problem with money as an incentive

Abstract

Abstract A Dynamic Dial-a-Ride Problem with Money as an Incentive (DARP-M) is a problem of finding optimal route to serve requests demand which uses taxi-sharing system with cost constraint. Taxi-sharing is a system where individual customer share vehicle with other customers, who has the same or similar origin, destination, and travel time. The optimal solution is the solution that can minimize the cost of each trip request. This study discusses DARP-M to optimize the use of taxi-sharing. The search for the DARP-M solution in this research uses the insertion heuristic method for construction of initial solution and the large neighborhood search method for the optimal solution determination. Then, the experiment uses three times periods, from which the experiment result shows the large neighborhood search method can minimize customers travel cost up to 27.40 % less than the cost of private rides.