Algorithm

Process (computing)

Engineering

Nondeterministic algorithm

Linear programming

Theoretical computer science

Operating system

Turing machine

Computation

Computer science

Mathematical optimization

Distributed computing

Integer programming

Psychology

Graph

Mathematics

Psychotherapist

Generality

Topology (electrical circuits)

Electrical engineering

Intelligent process planning (PP) is one of the most important components in an intelligent manufacturing system and acts as a bridge between product designing and practical manufacturing. PP is a nondeterministic polynomial-time (NP)-hard problem and, as existing mathematical models are not formulated in linear forms, they cannot be solved well to achieve exact solutions for PP problems. This paper proposes a novel mixed-integer linear programming (MILP) mathematical model by considering the network topology structure and the OR nodes that represent a type of OR logic inside the network. Precedence relationships between operations are discussed by raising three types of precedence relationship matrices. Furthermore, the proposed model can be programmed in commonly-used mathematical programming solvers, such as CPLEX, Gurobi, and so forth, to search for optimal solutions for most open problems. To verify the effectiveness and generality of the proposed model, five groups of numerical experiments are conducted on well-known benchmarks. The results show that the proposed model can solve PP problems effectively and can obtain better solutions than those obtained by the state-of-the-art algorithms.

A Novel MILP Model Based on the Topology of a Network Graph for Process Planning in an Intelligent Manufacturing System