This paper proposes an exact method to solve an integer indefinite quadratic bilevel problem with multiple objectives at the upper level, where the objective functions at both levels are a product of ...

My little theory is that the concept of “imprinting” in psychology can just as easily be applied to programming: Much as a baby goose decides that the first moving life-form it encounters is its ...

Abstract: This paper considers a Multi-Agent Motion Planning (MAMP) problem that seeks collision-free paths for multiple agents from their respective start to goal locations among static obstacles, ...

Abstract: In this paper, a design framework based on integer linear programming is proposed for optimizing sparse array structures. We resort to binary vectors to formulate the design problem for ...

HiGHS is a high performance serial and parallel solver for large scale sparse linear optimization problems of the form $$ \min \quad \dfrac{1}{2}x^TQx + c^Tx \qquad \textrm{s.t.}~ \quad L \leq Ax \leq ...

This paper presents a novel approach to the joint optimization of job scheduling and data allocation in grid computing environments. We formulate this joint optimization problem as a mixed integer ...

Once I started thinking about the apocalypse, it was hard to stop. An unsettling encounter with the doomsday clock that hangs over New York City’s Union Square got me frantically searching WikiHow for ...

ABSTRACT: This study proposes a novel approach to optimizing individual work schedules for book digitization using mixed-integer programming (MIP). By leveraging the power of MIP solvers, we aimed to ...

NVIDIA's cuOpt leverages GPU technology to drastically accelerate linear programming, achieving performance up to 5,000 times faster than traditional CPU-based solutions. The landscape of linear ...

Integer Linear Programming (ILP) is the foundation of combinatorial optimization, which is extensively applied across numerous industries to resolve challenging decision-making issues. Under a set of ...