Knowledge engineering mixed-integer linear programming: constraint typology

02/20/2021
by   Vicky Mak-Hau, et al.
0

In this paper, we investigate the constraint typology of mixed-integer linear programming MILP formulations. MILP is a commonly used mathematical programming technique for modelling and solving real-life scheduling, routing, planning, resource allocation, timetabling optimization problems, providing optimized business solutions for industry sectors such as: manufacturing, agriculture, defence, healthcare, medicine, energy, finance, and transportation. Despite the numerous real-life Combinatorial Optimization Problems found and solved, and millions yet to be discovered and formulated, the number of types of constraints, the building blocks of a MILP, is relatively much smaller. In the search of a suitable machine readable knowledge representation for MILPs, we propose an optimization modelling tree built based upon an MILP ontology that can be used as a guidance for automated systems to elicit an MILP model from end-users on their combinatorial business optimization problems.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
12/05/2022

Formulation of problems of combinatorial optimization for solving problems of management and planning of cloud production

The application of combinatorial optimization problems to solving the pr...
research
11/12/2020

A Knowledge Representation Approach to Automated Mathematical Modelling

Mathematicians formulate complex mathematical models based on user requi...
research
02/11/2020

Rapid Top-Down Synthesis of Large-Scale IoT Networks

Advances in optimization and constraint satisfaction techniques, togethe...
research
12/10/2022

Walkability Optimization: Formulations, Algorithms, and a Case Study of Toronto

The concept of walkable urban development has gained increased attention...
research
10/11/2018

A Resource Allocation based Approach for Corporate Mobility as a Service

Corporate mobility is often based on fixed assignments of vehicles to em...
research
10/26/2020

Interior Point Solving for LP-based prediction+optimisation

Solving optimization problems is the key to decision making in many real...

Please sign up or login with your details

Forgot password? Click here to reset