Results 41 to 50 of about 5,789 (193)

Multi-Objective Parallel Variable Neighborhood Search for Energy Consumption Scheduling in Blocking Flow Shops

IEEE Access, 2018
Blocking flow shop scheduling problem has been extensively studied because of its widespread industrial applications. However, the existing research mostly aims at makespan or total flow time minimization and ignores the criterion for energy saving. This
Fucai Wang, Guanlong Deng, Tianhua Jiang, Shuning Zhang   +3 more
doaj   +1 more source

On Two-machine Flow Shop Scheduling [PDF]

Journal of the Operations Research Society of China, 2014
In this note, we revisit the classical two-machine flow shop scheduling problem. A linear time approximation scheme is presented. For an online version with rejection, we propose best possible online algorithms.
Guochuan Zhang, Lin Chen, Wenchang Luo
openaire   +2 more sources

The Effectiveness of Genetic Algorithm, And the CDS Method In Solving Flowshop Scheduling Problems [PDF]

E3S Web of Conferences
Flow shop scheduling problem is considered NP-hard for m machines and n jobs. For such NP-hard combinatorial optimization problems, heuristics play a major role in searching for near-optimal solutions. In this paper we used Genetic Algorithm, and the CDS
Prassetiyo Hendro, Heryati Firda
doaj   +1 more source

Improve Algoritma Hodgson Untuk Meminimasi Jumlah Job Terlambat Pada Penjadwalan Flow shop

Jurnal Teknik Industri, 2018
Since Johnson published a paper in 1954, the problem of job scheduling has received the attention of hundreds of practitioners and researchers, as one of the most studied topics in Operation research.
Dian Setiya Widodo
doaj   +1 more source

A Note on Heuristics of Flow-Shop Scheduling [PDF]

Operations Research, 1996
We present an O(mn) two-group (TG) heuristic for the m-machine, n-job permutation flow-shop scheduling problem. We show that heuristic TG has a worst-case performance ratio of (m + 1)/2. We also establish worst-case bounds for several heuristics proposed in the past.
openaire   +2 more sources

Augmented ɛ‐constraint‐based matheuristic methodology for Bi‐objective production scheduling problems

IET Collaborative Intelligent Manufacturing
Matheuristic is an optimisation methodology that integrates mathematical approaches and heuristics to address intractable combinatorial optimisation problems, where a common framework is to insert mixed integer linear programming (MILP) models as local ...
Jiaxin Fan
doaj   +1 more source

Flow shop scheduling decisions through Techniques for Order Preference by Similarity to an Ideal Solution (TOPSIS)

International Journal of Production Management and Engineering, 2016
The flow-shop scheduling problem (FSP) has been widely studied in the literature and having a very active research area. Over the last few decades, a number of heuristic/meta-heuristic solution techniques have been developed.
Arun Gupta, Shailendra Kumar
doaj   +1 more source

A novel fuzzy model for multi-objective permutation flow shop scheduling problem with fuzzy processing time

Advances in Mechanical Engineering, 2019
This article proposes a novel fuzzy model for solving fuzzy multi-objective permutation flow shop scheduling problem with fuzzy processing time. Specifically, two fuzzy objectives, that is, the fuzzy makespan and the fuzzy total flow time, are taken into
Fuyu Yuan, Xin Xu, Minghao Yin
doaj   +1 more source

REVIEW ON JOB-SHOP AND FLOW-SHOP SCHEDULING USING

Journal of Mechanical Engineering, 2011
Scheduling is widely studied and complex combinatorial optimization problems. A vast amount of research has been performed in this particular area to effectively schedule jobs for various objectives. The multi-criteria scheduling problem is one of the main research subjects in the field of modern manufacturing where most of them are considered as NP ...
Hafiz Ullah, Sultana Parveen
openaire   +3 more sources

A computational efficient optimization of flow shop scheduling problems. [PDF]

Sci Rep, 2022
Liang Z, Zhong P, Liu M, Zhang C, Zhang Z.   +4 more
europepmc   +1 more source