A sequencing problem with family setup times
Discrete Applied Mathematics
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Two-machine flowshop group scheduling problem
Computers and Operations Research
Fuzzy scheduling with application to real-time systems
Fuzzy Sets and Systems
A genetic algorithm to minimize maximum lateness on a batch processing machine
Computers and Operations Research
The single machine ready time scheduling problem with fuzzy processing times
Fuzzy Sets and Systems - Special issue: Optimization and decision support systems
A genetic algorithm for solving economic lot size scheduling problem
Computers and Industrial Engineering - 26th International conference on computers and industrial engineering
Improved genetic algorithm for the permutation flowshop scheduling problem
Computers and Operations Research
Parallel machine scheduling models with fuzzy processing times
Information Sciences—Informatics and Computer Science: An International Journal
Two-machine flowshop scheduling with job class setups to minimize total flowtime
Computers and Operations Research
Mixed integer formulation to minimize makespan in a flow shop with batch processing machines
Mathematical and Computer Modelling: An International Journal
An effective neighborhood search algorithm for scheduling a flow shop of batch processing machines
Computers and Industrial Engineering
Advances in Engineering Software
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In this paper, we present a mixed-integer fuzzy programming model and a genetic algorithm (GA) based solution approach to a scheduling problem of customer orders in a mass customizing furniture industry. Independent job orders are grouped into multiple classes based on similarity in style so that the required number of setups is minimized. The family of jobs can be partitioned into batches, where each batch consists of a set of consecutively processed jobs from the same class. If a batch is assigned to one of available parallel machines, a setup is required at the beginning of the first job in that batch. A schedule defines the way how the batches are created from the independent jobs and specifies the processing order of the batches and that of the jobs within the batches. A machine can only process one job at a time, and cannot perform any processing while undergoing a setup. The proposed formulation minimizes the total weighted flowtime while fulfilling due date requirements. The imprecision associated with estimation of setup and processing times are represented by fuzzy sets.