Clover Optimization provides decision support software that integrates vehicle routing and container loading algorithms to enhance logistics planning efficiency. By addressing the complexities of load and route planning, their technology enables logistics companies to achieve time savings of 30% to 80% and reduce transport costs by 5% to 25%.
Funding
Funding not disclosed
Founders
Product
Problem
Logistics companies face increasing complexity in load and route planning due to time and resource constraints. Traditional tour planning solutions often overlook load planning, resulting in inefficient use of vehicle capacity and increased transportation costs. This leads to planning uncertainty and difficulties in meeting specific delivery requirements.
Solution
Clover Optimization provides decision support software that integrates container loading and vehicle routing algorithms to optimize transport management. Their solution considers constraints such as stacking rules, load capacity, axle load limits, and loading/unloading sequence requirements to generate efficient load plans. The software also allows for dynamic dispatching, taking into account time windows, order splitting, pick-up and delivery priorities, and heterogeneous vehicle fleets. By optimizing both loading and routing in a single step, Clover Optimization enables logistics companies to reduce planning time and transportation costs while increasing planning reliability.
Target Audience
Clover Optimization serves dispatchers, transport companies, and logistics software providers seeking to optimize their planning processes and reduce transportation costs.
Features
- 3D load planning that optimizes container loading considering stacking rules, load capacity, and axle load limits.
- Dynamic tour planning that utilizes customizable optimization goals and considers time windows and delivery priorities.
- Integrated load and tour planning, optimizing both processes in a single step.
- REST API for integration with existing Transport Management Systems (TMS) and Warehouse Management Systems (WMS).
- Metaheuristic algorithms combined with greedy heuristics, local search, and tree search methods for efficient planning.
- Ability to use container loading and vehicle routing algorithms independently.