Integrated process planning and scheduling with minimizing total tardiness in multi-plants supply chain

Authors:
Chiung Moon;Jongsoo Kim;Sun Hur
Affiliations:
Department of Industrial Engineering, Hanyang University, Ansan 425-791, South Korea;Department of Industrial Engineering, Hanyang University, Ansan 425-791, South Korea;Department of Industrial Engineering, Hanyang University, Ansan 425-791, South Korea
Venue:
Computers and Industrial Engineering - Supply chain management
Year:
2002

Citing 3
Cited 16

Fundamentals of data structures in PASCAL

Fundamentals of data structures in PASCAL
Process planning and scheduling—a method of integration for productivity improvement

Computers and Industrial Engineering
Genetic Algorithms

Genetic Algorithms

A simulated annealing approach to a bi-criteria sequencing problem in a two-stage supply chain

Computers and Industrial Engineering
Integrated process planning and scheduling in a supply chain

Computers and Industrial Engineering
A model for evaluating a design change and the distributed manufacturing operations in a collaborative manufacturing environment

Computers in Industry
Applications of particle swarm optimisation in integrated process planning and scheduling

Robotics and Computer-Integrated Manufacturing
A modified particle swarm optimization for production planningproblems in the TFT Array process

Expert Systems with Applications: An International Journal
The distributed permutation flowshop scheduling problem

Computers and Operations Research
A simulated annealing approach to a bi-criteria sequencing problem in a two-stage supply chain

Computers and Industrial Engineering
A hybrid approach for supplier cluster analysis

Computers & Mathematics with Applications
Review article: A review of soft computing applications in supply chain management

Applied Soft Computing
A novel genetic algorithm for solving production and transportation scheduling in a two-stage supply chain

Computers and Industrial Engineering
A genetic approach to two-phase optimization of dynamic supply chain scheduling

Computers and Industrial Engineering
Agent-based model for decision support in multi-site manufacturing enterprises

MATES'09 Proceedings of the 7th German conference on Multiagent system technologies
Simulation-based business decision support for multi-site supply chain management

SpringSim '10 Proceedings of the 2010 Spring Simulation Multiconference
A genetic algorithm for vendor managed inventory control system of multi-product multi-constraint economic order quantity model

Expert Systems with Applications: An International Journal
Scheduling optimisation for supply chain in networked manufacturing

International Journal of Computer Applications in Technology
Solving a multi-objective master planning problem with substitution and a recycling process for a capacitated multi-commodity supply chain network

Journal of Intelligent Manufacturing

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we propose an integrated process planning and scheduling (IPPS) model for the multi-plant supply chain (MSC), which behaves like a single company through strong coordination and cooperation toward mutual goals. The IPPS problem is one of the most important issues for supporting the global objectives, because the function takes part in the assignment of factory resources to production tasks. The problem is formulated as a mathematical model considering alternative machines and sequences, sequence-dependent setup, and distinct due dates. The objective of the model is to decide the schedules for minimizing total tardiness through analysis of the alternative machine selection and the operation sequences in MSC. In order to obtain good approximate solutions, genetic algorithm-based heuristic approach is developed. Numerical experiments are carried out to demonstrate the efficiency of the proposed approach.