Solving Group Scheduling Problem in No-wait Flow Shop with Sequence Dependent Setup Times

نویسندگان

  • Abolfazl Adressi Department of Industrial Engineering, K.N.Toosi University of Technology, Iran
  • Reza Bashirzadeh Department of Industrial Engineering, K.N.Toosi University of Technology, Iran
  • Saeed Tasouji Hassanpour Faculty of Industrial Engineering, Tarbiat Modares University (TMU), Iran, Tehran
  • Vahid Azizi Department of Industrial Engineering, K.N.Toosi University of Technology, Iran
چکیده مقاله:

Different manufacturing enterprises use regularly scheduling algorithms in order to help meeting demands over time and reducing operational costs. Nowadays, for a better useofresources and manufacturingin accordance withcustomer needs and given the level ofcompetitionbetweencompanies, employing asuitablescheduling programhasa double importance. Conventional productionmethods are constantly substituted with new ones for improving the efficiency and effectiveness of the entire production system. In this paper, two Meta-heuristic algorithms, Genetic and simulated annealing, have been used in order to solve the group scheduling problem of jobs in a single stage No-wait flow shop environment in which setup times are sequence dependent,. The purpose of solving the proposed problem is to minimize the maximum time needed to complete the jobs (Makespan). The results show that Genetic algorithm is efficient in problems with small and large dimensions, with respect to time parameter of problem solving.

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

solving group scheduling problem in no-wait flow shop with sequence dependent setup times

different manufacturing enterprises use regularly scheduling algorithms in order to help meeting demands over time and reducing operational costs. nowadays, for a better useofresources and manufacturingin accordance withcustomer needs and given the level ofcompetitionbetweencompanies, employing asuitablescheduling programhasa double importance. conventional productionmethods are constantly subs...

متن کامل

Solving Re-entrant No-wait Flow Shop Scheduling Problem

In this study, we consider the production environment of no-wait reentrant flow shop with the objective of minimizing makespan of the jobs. In a reentrant flow shop, at least one job should visit at least one of the machines more than once. In a no-wait flowshop scheduling problem, when the process of a specific job begins on the first machine, it should constantly be processed without waiting ...

متن کامل

an assembly flow-shop scheduling problem with sequence-dependent setup and transportation times

in this paper, three-stage assembly flowshop scheduling is considered with respect to minimizing bi-objectives, namely mean flow time and mean tardiness. this problem is a model of production systems, which several production operations are done simultaneously and independently, and then produced components are collected and transferred to an assembly stage for the final operation. in this mode...

متن کامل

New scheduling rules for a dynamic flexible flow line problem with sequence-dependent setup times

In the literature, the application of multi-objective dynamic scheduling problem and simple priority rules are widely studied. Although these rules are not efficient enough due to simplicity and lack of general insight, composite dispatching rules have a very suitable performance because they result from experiments. In this paper, a dynamic flexible flow line problem with sequence-dependent se...

متن کامل

منابع من

با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ذخیره در منابع من قبلا به منابع من ذحیره شده

{@ msg_add @}


عنوان ژورنال

دوره 3  شماره 1

صفحات  5- 16

تاریخ انتشار 2014-02-01

با دنبال کردن یک ژورنال هنگامی که شماره جدید این ژورنال منتشر می شود به شما از طریق ایمیل اطلاع داده می شود.

میزبانی شده توسط پلتفرم ابری doprax.com

copyright © 2015-2023