Distributed Constraint Optimisation and Search Algorithms form a vital framework for addressing complex decision‐making and scheduling problems in multi-agent systems.

The researchers also considered an extension of the STSP that includes time windows for simultaneous pickups and deliveries, creating a more realistic and challenging problem. The core method involves ...

We present an implementable algorithm for solving constrained optmization problems defined by functions that are not everywhere differentiable. The method is based on combining, modifying and ...

Sequential optimality conditions for constrained optimization are necessarily satisfied by local minimizers, independently of the fulfillment of constraint qualifications. These conditions support the ...

Implicit Hitting Set Algorithms for Constraint Optimization Computationally hard optimization problems are commonplace not only in theory but also in practice in many real-world domains. Even ...

Students will learn about the most common numerical optimization algorithms for solving smooth unconstrained and constrained optimization problems. They will understand the theoretical foundation and ...

In addition, the book includes an introduction to artificial neural networks, convex optimization, multi-objective optimization and applications of optimization in machine learning. About the Purdue ...

M.Sc. Paul Saikko succesfully defended his doctoral dissertation Im­pli­cit Hit­ting Set Algorithms for Con­straint Op­tim­iz­a­tion on December 2, 2019. The thesis work was conducted in the ...