The modern battlefield demands a new breed of Soldier, one equipped not just with physical prowess but also with the ability ...

Imagine an operational environment in the near future. Inside a main command post, a decision is made quickly but agonizingly ...

The demand on businesses to act instantaneously with the data has never been greater in the current digital first economy.

Comparing Modeling Approaches for Distributed Contested Logistics. American Journal of Operations Research, 15, 125-145. doi: ...

By reformulating the linear multiplicative programming problem (LMP) as an equivalent nonconvex programming problem (EP), we present a new accelerating outcome space branch-and-bound algorithm for ...

We formulate this problem as a nonlinear Generalized Disjunctive Program (GDP), which, following transformation, results in a large-scale mixed-integer nonlinear programming (MINLP) problem. This ...

Many operation optimization problems such as scheduling and assignment of interest to the automation community are mixed-integer linear programming (MILP) problems. Because of their combinatorial ...

Linear Programming: Basics, Simplex Algorithm, and Duality. Applications of Linear Programming: regression, classification and other engineering applications. Integer Linear Programming: Basics, ...

Problem definition: Last-mile delivery is a critical component of logistics networks, accounting for approximately 30%–35% of costs. As delivery volumes have increased, truck route times have become ...