What is Computational Logistics?

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  • Written By: Shannon Kietzman
  • Edited By: Niki Foster
  • Last Modified Date: 06 October 2019
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Computational logistics involves the planning and implementation of large and complex tasks using computations and higher mathematics. Computational logistics is used in many areas, including the flow and storage of goods, services, and related information from their point of origin to the point of consumption. In military operations, computational logistics involves the organization and planning of the movement of military troops, their equipment, and their supplies to ensure minimal loss of personnel or property.

In computational logistics, optimization models and algorithms must be developed and verified for the plan and execution of complex logistics and supply chain systems. An optimization model consists of an objective function and a set of constraints in the form of a system of equations or inequalities. An algorithm is the procedure for executing a task that, given an initial state, will terminate in a defined end state. These models and algorithms are integrated with advanced computer technology to form high-speed interaction strategies for large scale problem solving.

The transportation industry is an increasingly complex system that makes use of computational logistics. The use of computers, models, and algorithms helps to create the most efficient scheduling and planning for the transport of passengers and consumer products.


The prediction of weather systems, seismic disturbances, and global climate changes has advanced significantly through computational logistics. Supercomputers can create models that take into account the wide variety of factors affecting the earth’s complex environmental system. This use of computational logistics helps us to understand and live more safely in our environment.

Computational logistics plays an important and growing role in the field of national and world health. Increasingly advanced computers and mathematics techniques make possible more accurate long term predictions in health studies involving the effectiveness of medications, treatments, and changes in lifestyle or diet. Computational logistics is also critical in planning and being prepared for a possible future health crisis so there will be minimal loss of life.


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