INSIGHTS

Experience in dredging

Specializations like dredging and environmental remediation are rare. Many decision challenges exist in large multi-vessel projects, algorithms for modern optimization can help plan project planning. Dredgers must mobilize multiple vessels for weeks or months, determining the best way to do this is a complex process. Variable vessel production rates make hand-planning nearly impossible (and depending on zone characteristics). The planning challenge for Solvice was to reduce overall operation costs while considering design characteristics.

Dredging, marine engineering, and environmental remediation are just a few of the highly specialized fields in which only a few operate. Engineers working on large-scale multi-vessel projects face a challenge in determining the optimal project plan while taking into account multiple technical constraints and business requirements. State-of-the-art optimization algorithms can be leveraged to create an optimal project plan.


As a leading dredging company, multiple vessels must be mobilized for weeks or even months in order to complete some dredging projects. As a result of these projects, various zones must be dredged concurrently, while others must be produced in a predetermined order. Historically, engineering staff have been heavily burdened with the planning of such projects. Additionally, due to the variable production rates per vessel, it is no longer possible to plan cost-effective projects solely by hand (and depending on zone characteristics).


For one of the market leaders in the dredging industry, Solvice conducted a thorough analysis of the planning challenge, taking into account the design characteristics of each project (volumes to be dredged or discharged), technical constraints (e.g. zones that must be processed in a specific order, vessels that can operate concurrently in a zone), and the primary business driver: minimizing overall production costs. As a result, Solvice developed an algorithm for future dredging projects as well as to simulate the impact of key cost drivers.