Minimizing the total tardiness and job rejection cost in a proportionate flow shop with generalized due dates

2021 ◽  
Author(s):  
Baruch Mor ◽  
Gur Mosheiov ◽  
Dvir Shabtay
Keyword(s):  
Flow Shop ◽  
Total Tardiness ◽  
Due Dates ◽  
Job Rejection ◽  
Rejection Cost ◽  
Proportionate Flow Shop

Computational Study of N-Job M-Machine Flow Shop Scheduling Problems: SPT, EDD, NEH, NEH-EDD, and Modified-NEH Algorithms

2017 ◽  
Vol 16 (04) ◽  
pp. 375-384
Author(s):  
Dwi Agustina Kurniawati ◽  
Yoga Isnaini Nugroho
Keyword(s):  
Flow Shop ◽  
Computational Study ◽  
Total Tardiness ◽  
Flow Shop Scheduling ◽  
Small Data ◽  
Data Sets ◽  
Scheduling Problems ◽  
Due Dates ◽  
Shop Scheduling ◽  
Small Data Sets

This paper discusses about the flow shop scheduling problems using shortest processing time, earliest due date (EDD), Nawaz, Enscore, and Ham (NEH), NEH-EDD, and modified-NEH methods. The objective of this research is to determine the performance of these methods in minimizing makespan and total tardiness. Processing times and due dates were randomly generated, and computational studies were performed in Microsoft Visual Basic 6.0. The experiments are performed for small and medium data sets. Efficiency index, relative error, and run time measure the performance of each method. Experimental results showed that NEH has the best performance in minimizing the makespan in both data sets; these are 53.35 time unit for small data sets and 83.803 time unit for medium data sets. NEH-EDD has the best performance in minimizing total tardiness with 9.37 time unit for small data sets and 231.02 time unit for medium data sets. Modified-NEH, as the proposed method for minimizing makespan and total tardiness at the same time, has good enough result. For minimizing the makespan, modified-NEH results in 57.15 time unit for small data sets and 88.107 time unit for medium data sets. For minimizing total tardiness, the modified-NEH results in 14.21 time unit for small data sets and 246.57 time unit for medium sets.

Scheduling a Single Machine with Job Rejection and Multiple Common due Dates Assignment

2014 ◽  
Vol 644-650 ◽  
pp. 2034-2037
Author(s):  
Zhuo Fang ◽  
Cheng Xin Luo
Keyword(s):  
Dynamic Programming ◽  
Single Machine ◽  
Single Machine Scheduling ◽  
Due Dates ◽  
Due Date ◽  
Optimal Sequence ◽  
Job Rejection ◽  
Rejection Cost ◽  
Programming Algorithms ◽  
Rejection Penalty

This paper studies a single machine scheduling with job rejection and multiple common due dates assignment. A job is either rejected, in which a rejection penalty has to be paid, or accepted and processed on the machine. There is a cost if the job is completed prior or after the due date. The objective is to determine the optimal due dates, the set of jobs assigned to each due date and the optimal sequence of jobs to minimize a total costs based on earliness, tardiness, multiple common due dates and rejection cost. We provide dynamic programming algorithms and show that the problem is solvable in polynomial time.

On Flow Shop Scheduling with Release and Due Dates to Minimize Maximum Lateness

1983 ◽  
Vol 34 (7) ◽  
pp. 615 ◽  
Author(s):  
Jozef Grabowski ◽  
Ewa Skubalska ◽  
Czeslaw Smutnicki
Keyword(s):  
Flow Shop ◽  
Maximum Lateness ◽  
Flow Shop Scheduling ◽  
Due Dates ◽  
Shop Scheduling

scholarly journals Analisis Perbandingan Aggregat Of Function (AOF) dengan Non-Dominated Sorting Genetic Algorithm (NSGA-II) dalam Menentukan Optimasi Multi-Objective pada Penjadwalan Mesin Produksi Flow Shop

2018 ◽  
Vol 17 (2) ◽  
pp. 158
Author(s):  
Fifin Sonata ◽  
Dede Prabowo Wiguna
Keyword(s):  
Genetic Algorithm ◽  
Flow Shop ◽  
Total Tardiness ◽  
Pareto Optimal ◽  
Nsga Ii ◽  
Trade Off ◽  
Multi Objective

Penjadwalan mesin produksi dalam dunia industri memiliki peranan penting sebagai bentuk pengambilan keputusan. Salah satu jenis sistem penjadwalan mesin produksi adalah sistem penjadwalan mesin produksi tipe flow shop. Dalam penjadwalan flow shop, terdapat sejumlah pekerjaan (job) yang tiap-tiap job memiliki urutan pekerjaan mesin yang sama. Optimasi penjadwalan mesin produksi flow shop berkaitan dengan penyusunan penjadwalan mesin yang mempertimbangkan 2 objek yaitu makespan dan total tardiness. Optimasi kedua permasalahan tersebut merupakan optimasi yang bertolak belakang sehingga diperlukan model yang mengintegrasikan permasalahan tersebut dengan optimasi multi-objective A Fast Elitist Non-Dominated Sorting Genetic Algorithm for Multi-Objective Optimazitaion : NSGA-II. Dalam penelitian ini akan dibandingkan 2 buah metode yaitu Aggregat Of Function (AOF) dengan NSGA-II agar dapat terlihat nilai solusinya. Penyelesaian penjadwalan mesin produksi flow shop dengan algoritma NSGA-II untuk membangun jadwal dengan meminimalkan makespan dan total tardiness.Tujuan yang ingin dicapai adalah mengetahui bahwa model yang dikembangkan akan memberikan solusi penjadwalan mesin produksi flow shop yang efisien berupa solusi pareto optimal yang dapat memberikan sekumpulan solusi alternatif bagi pengambil keputusan dalam membuat penjadwalan mesin produksi yang diharapkan. Solusi pareto optimal yang dihasilkan merupakan solusi optimasi multi-objective yang optimal dengan trade-off terhadap seluruh objek, sehingga seluruh solusi pareto optimal sama baiknya.

scholarly journals Penjadwalan Flow Shop untuk Meminimasi Total Tardiness Menggunakan Algoritma Cross Entropy–Algoritma Genetika

2019 ◽  
Vol 18 (2) ◽  
pp. 133 ◽  
Author(s):  
Dana Marsetiya Utama ◽  
Leo Rizki Ardiansyah ◽  
Annisa Kesy Garside
Keyword(s):  
Flow Shop ◽  
Total Tardiness ◽  
Cross Entropy

Two-Machine Ordered Flow Shop Scheduling with Generalized Due Dates

2020 ◽  
Vol 37 (01) ◽  
pp. 1950032
Author(s):  
Myoung-Ju Park ◽  
Byung-Cheon Choi ◽  
Yunhong Min ◽  
Kyung Min Kim
Keyword(s):  
Flow Shop ◽  
Flow Shop Scheduling ◽  
Due Dates ◽  
Shop Scheduling ◽  
Processing Times ◽  
Specific Position ◽  
Polynomially Solvable ◽  
Definition Of ◽  
Tardy Jobs ◽  
Np Hardness

We consider a two-machine flow shop scheduling with two properties. The first is that each due date is assigned for a specific position different from the traditional definition of due dates, and the second is that a consistent pattern exists in the processing times within each job and each machine. The objective is to minimize maximum tardiness, total tardiness, or total number of tardy jobs. We prove the strong NP-hardness and inapproximability, and investigate some polynomially solvable cases. Finally, we develop heuristics and verify their performances through numerical experiments.

Review of the ordered and proportionate flow shop scheduling research

2013 ◽  
Vol 60 (1) ◽  
pp. 46-55 ◽  
Author(s):  
S.S. Panwalkar ◽  
Milton L. Smith ◽  
Christos Koulamas
Keyword(s):  
Flow Shop ◽  
Flow Shop Scheduling ◽  
Shop Scheduling ◽  
Proportionate Flow Shop
Sign in / Sign up

Export Citation Format

Share Document