Some details
Our customer was one of the prominent logistics company based out of the USA. An optimal resource planning for a logistics company is crucial as they have to manage hundreds of containers, carrier trucks, courier vans, delivery routes, laborers etc. Our customer wanted a solution to optimize the efficiency of their resource allocation and job scheduling.
We designed an intelligent resource allocation algorithm that
would be able to consider different factors like the available capacity of a particular resource while mapping the consignment to the most ideal resource for the planning, routing, and scheduling of resources. We designed a system based on genetic algorithm, which has the capacity to select the resources judiciously, striking a balance between over-burdening and idle time. The algorithm is an ideal solution to combinatorial problems with multiple objectives. It has the flexibility to address complex issues, as there could be instances when the number of activities, resource types, and execution modes increases in a resource allocation problem. The genetic algorithm can be effectively used to minimize the costs that arise from over-allocation of resources, everyday resource fluctuations, and exceeding of project deadlines. We recognized that a system based on the Genetic algorithm is the ideal solution for optimization problems with constraints.