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.
Resource allocation or resource planning is the process of assigning and managing assets of an organization in a manner that it supports the organization’s strategic goals. It includes managing tangible assets such as hardware to make the best use of intangible assets such as human capital. It also involves balancing competing needs and priorities and determining the most effective course of action in order to maximize the effective use of limited resources and gain the best return on investment. Our client faced the same problem and was looking for a solution that takes into account all parameters like available resources, routes, and timelines and prepares an optimal plan for doing the job.
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.
The projected results indicate a considerable improvement in resource efficiency. An added advantage of our design was that it took into consideration constraints like schedule planning, capacity planning, and route optimization, and allocated the resources intelligently. This resulted in more orders being fulfilled in a shorter span of time. Feedback from the managers shows that the efficiency of the whole logistics set-up has improved after following such a design for resource allocation. Most importantly, the solution helped to avoid the under or overutilization of staff in the organization. The effective resource management solution has also helped in assessing how well the resources have been utilized on a daily, weekly, or monthly basis. By allocating resources judiciously not only can the management evaluate resource utilization, but also identify skill shortages and training requirements. A centrally managed system for resource allocation will help companies to reduce administration costs, and replace outdated systems. The biggest advantage as seen in our existing clientele is the enhanced earning potential and better customer relationships.