Logistics Management

AI-powered Resource Planning Tool

THE CLIENT

Our customer was a prominent logistics company operating primarily in the US. For a logistics company, it is crucial to follow optimal resource planning, as they have to manage hundreds of containers, carrier trucks, courier vans, delivery routes, and laborers on a daily basis. Our task was to provide our client with a solution, to optimize the efficiency of their resource allocation and job scheduling.

THE SCENARIO

Resource allocation or resource planning is the process of assigning and managing assets of an organization to meet and support organizational strategic goals. The business followed its intuition in resource planning which quite often failed to be profitable. Figuring out the right resource allocation plan was the major problem faced by our client and they wanted to have a solution to help with the management of tangible assets such as hardware to make the best use of intangible assets such as human capital.

THE BUSINESS CHALLENGES

The client was looking for a solution that could consider all the parameters like

THE SOLUTION

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 a 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 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.

BENEFITS OFFERED

TRANSFORMATION PROCESS

DiscoveryThe client realized that the current Logistics process is not efficient. It wastes a lot of resources and thus reduces the profit margin of the company.
Consultation with Accubits Blockchain Experts Our client shared their problem statement with Accubits. An expert team of solution architects and business analysts conducted a study to analyze the problem statements, technical feasibility and proposed a few options using cutting-edge technologies to solve these issues. Each option accompanied details such as the cost to implement, estimated benefit, requirements for implementation, etc,
Review of potential solutionsConsidering different parameters such as ETA for deployment, project requirements from the client, etc, the Client opted to integrate Al into their current system.
Impact analysisA detailed impact analysis was required before integrating the algorithm into the current logistics process. In the analysis, all dependencies including server requirements, internal positioning was defined and studied their potential impact on the existing system. After the impact analysis, a clear-cut implementation strategy was defined.
Post-deployment modificationsThe performance of the solution was evaluated and fine-tuned the solution with post-deployment modifications

THE RESULTS

The results showed a drastic 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.

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Highlights

Genetic algorithm based scheduler

Optimal schedule planning

Optimal capacity planning

Optimal route optimization

Intelligent resource allocation

Technologies Used