Mathematical formulations for scheduling jobs on identical parallel machines with family setup times and total weighted completion time minimization

Scheduling Identical Parallel Machines to Minimize Total Weighted Completion Time

A New ILP Model for Identical Parallel-Machine Scheduling with Family Setup Times Minimizing the Total Weighted Flow Time by a Genetic Algorithm

This paper presents a novel, integer-linear programming (ILP) model for an identical parallel-machine scheduling problem with family setup times that minimizes the total weighted flow time (TWFT). Some researchers have addressed parallel-machine scheduling problems in the literature over the last three decades. However, the existing studies have been limited to the research of independent jobs,...

Scheduling jobs on parallel machines with sequence-dependent setup times

The study considers the scheduling problem of identical parallel machines subject to minimization of the maximumcompletion time and the maximum tardiness expressed in a linear convex objective function. The maximum completiontime or makespan is the date when the last job to be completed leaves the system. The maximum tardiness is indicated bythe job that is completed with the lo...

Scheduling Multiple Families of Jobs on Parallel Machines to Minimize Total Weighted Completion Time

We consider the problem of scheduling multiple families of jobs on identical parallel machines to minimize the total weighted completion time of the jobs. In this problem, a setup time is necessary whenever a job from one family is processed immediately after another job from a di erent family. The setup time could be sequence independent or sequence dependent. We propose a column generation ba...

An Iterated Greedy Algorithm for Flexible Flow Lines with Sequence Dependent Setup Times to Minimize Total Weighted Completion Time

This paper explores the flexile flow lines where setup times are sequence- dependent. The optimization criterion is the minimization of total weighted completion time. We propose an iterated greedy algorithm (IGA) to tackle the problem. An experimental evaluation is conducted to evaluate the proposed algorithm and, then, the obtained results of IGA are compared against those of some other exist...