Constraint programming (CP) is a programming paradigm where relations between variables are stated in the form of constraints. It's particularly useful for solving complex combinatorial problems such ...

Abstract: In the linear programming approach to approximate dynamic programming, one tries to solve a certain linear program - the ALP -, which has a relatively small number K of variables but an ...

Constraint Programming (CP) has been successful in a number of combinatorial search and discrete optimisation problems. Yet other more traditional approaches, such as Integer Programming (IP), can ...

Linear semi-infinite programming (LSIP) is a branch of optimisation that focuses on problems where a finite number of decision variables is subject to infinitely many linear constraints. This ...

Task 1 (task1.py) - Develop a constraint satisfaction model that solves the following logical puzzle: James, Daniel, Emily, and Sophie go out for dinner. They all order a starter, a main course, a ...

A study focuses on a linear programming problem that involved a special fuzzy relation inequality (FRI) system, herein referred to as a secondary maximum minimum (SecMaxMin) FRI system. The SecMax-Min ...

Linear multiplicative models are popular tools for analyzing data with positive responses. However, the linear structure of models is too restrictive on the regression relation, which may lead to a ...