Scheduling of Flow-Shop, Job-Shop, and Combined Scheduling Problems using MOEAs with Fixed and Variable Length Chromosomes

2007 ◽  
pp. 49-99 ◽  
Author(s):  
Mark P. Kleeman ◽  
Gary B. Lamont
Keyword(s):  
Job Shop ◽  
Flow Shop ◽  
Variable Length ◽  
Scheduling Problems

scholarly journals A COMPARATIVE STUDY OF THE USABILITY OF DIFFERENT PRODUCTION SCHEDULING ALGORITHMS AND RULES

2021 ◽  
Vol 2 ◽  
pp. 41-46
Author(s):  
Pavol Jurík
Keyword(s):  
Production Process ◽  
Production Scheduling ◽  
Job Shop ◽  
Flow Shop ◽  
Production Systems ◽  
Scheduling Problems ◽  
History Of ◽  
Service Object ◽  
The Right ◽  
Production Plans

Production scheduling optimization is a very important part of a production process. There are production systems with one service object and systems with multiple service objects. When using several service objects, there are systems with service objects arranged in a parallel or in a serial manner. We also distinguish between systems such as flow shop, job shop, open shop and mixed shop. Throughout the history of production planning, a number of algorithms and rules have been developed to calculate optimal production plans. These algorithms and rules differ from each other in the possibilities and conditions of their application. Since there are too many possible algorithms and rules it is not easy to select the proper algorithm or rule for solving a specific scheduling problem. In this article we analyzed the usability of 33 different algorithms and rules in total. Each algorithm or rule is suitable for a specific type of problem. The result of our analysis is a set of comparison tables that can serve as a basis for making the right decision in the production process decision-making process in order to select the proper algorithm or rule for solving a specific problem. We believe that these tables can be used for a quick and easy selection of the proper algorithm or rule for solving some of the typical production scheduling problems.

scholarly journals Application of genetic algorithm to industrial scheduling and problems of parameters evaluation

2021 ◽  
Vol 47 ◽  
Author(s):  
Edgaras Šakurovas ◽  
Narimantas Listopadskis
Keyword(s):  
Genetic Algorithm ◽  
Job Shop ◽  
Flow Shop ◽  
Np Hard ◽  
Scheduling Problems ◽  
Optimal Parameters ◽  
Algorithm Performance ◽  
Hard Problems ◽  
Np Hard Problems ◽  
Real World Problems

Genetic algorithms are widely used in various mathematical and real world problems. They are approximate metaheuristic algorithms, commonly used for solving NP-hard problems in combinatorial optimisation. Industrial scheduling is one of the classical NP-hard problems. We analyze three classical industrial scheduling problems: job-shop, flow-shop and open-shop. Canonical genetic algorithm is applied for those problems varying its parameters. We analyze some aspects of parameters such as selecting optimal parameters of algorithm, influence on algorithm performance. Finally, three strategies of algorithm – combination of parameters and new conceptualmodel of genetic algorithm are proposed.

A DYNAMIC APPROACH OF USING DISPATCHING RULES IN SCHEDULING

2016 ◽  
Vol 78 (6) ◽  
Author(s):  
Khaled Ali Abuhasel
Keyword(s):  
Processing Time ◽  
Job Shop ◽  
Flow Shop ◽  
Job Shop Scheduling ◽  
Working Environment ◽  
Dispatching Rules ◽  
Scheduling Problems ◽  
Changing Environment ◽  
Environment Simulation ◽  
Made In

Manufacturing system in reality has dynamic nature due to certain unexpected events occur in changing environment, which requires rescheduling. This does not mean that every decision is made in real time. Based on the state of the working environment, determining best rule at right time is one of the alternatives.  This study focuses on selecting the dispatching rule that show best performance dynamically both in static and changing environment.  Simulation is carried out by employing genetic algorithm on flow-shop and job-shop scheduling problems to compare the performance of the dispatching rules dynamically. Out of many rules proposed in the past, it has been observed that under certain conditions, the SPT (shortest processing time) performs best in both the environment, when the total processing time of a job is not high relatively.  

scholarly journals Some Results on Shop Scheduling with S-Precedence Constraints among Job Tasks

Algorithms ◽  
2019 ◽  
Vol 12 (12) ◽  
pp. 250 ◽  
Author(s):  
Alessandro Agnetis ◽  
Fabrizio Rossi ◽  
Stefano Smriglio
Keyword(s):  
Job Shop ◽  
Flow Shop ◽  
Exact Algorithms ◽  
Precedence Constraints ◽  
Flow Shop Scheduling ◽  
Scheduling Problems ◽  
Job Tasks ◽  
Shop Scheduling ◽  
Special Cases ◽  
Complexity Status

We address some special cases of job shop and flow shop scheduling problems with s-precedence constraints. Unlike the classical setting, in which precedence constraints among the tasks of a job are finish–start, here the task of a job cannot start before the task preceding it has started. We give polynomial exact algorithms for the following problems: a two-machine job shop with two jobs when recirculation is allowed (i.e., jobs can visit the same machine many times), a two-machine flow shop, and an m-machine flow shop with two jobs. We also point out some special cases whose complexity status is open.

Application of Ontology in Event-Driven Job-Shop Scheduling Problems

2015 ◽  
Vol 775 ◽  
pp. 458-463 ◽  
Author(s):  
Xiang Min Xu ◽  
Xi Fan Yao
Keyword(s):  
Job Shop ◽  
Flow Shop ◽  
Job Shop Scheduling ◽  
Flow Shop Scheduling ◽  
Scheduling Problem ◽  
Scheduling Problems ◽  
Job Shop Scheduling Problem ◽  
Shop Scheduling ◽  
Event Driven ◽  
Flexible Flow Shop Scheduling

Aiming at the flexible flow-shop scheduling problem of cloud manufacturing, this paper introduces event driven concept and apply ontologies to Job-Shop scheduling problem FT46. The inference of ontology models allows the system to gain the dynamic information of workshop, and then rule engine is used to match event patterns to optimize the job shop scheduling problem.

scholarly journals Analysis of usage of genetic and tabu search algorithms in shop scheduling

2008 ◽  
Vol 48 ◽  
Author(s):  
Edgaras Šakurovas ◽  
Narimantas Listopadskis
Keyword(s):  
Genetic Algorithms ◽  
Tabu Search ◽  
Real World ◽  
Job Shop ◽  
Flow Shop ◽  
Proper Time ◽  
Search Algorithms ◽  
Scheduling Problem ◽  
Scheduling Problems ◽  
Shop Scheduling

A wide area of scheduling problem is industrial so-called shop scheduling (Job Shop, Flow Shop and Open Shop) which has important applications in real world industrial problems. Metaheuristic algorithms(Genetic and Tabu search algorithms in this case) seem to be one of the best candidates for finding nearbyoptima in proper time. In this work we implemented several genetic algorithms (separated by values oftheir parameters) and several Tabu search algorithms (separated by neighborhood of solution). Finally, implemented eight algorithms are examined for random shop scheduling problems in terms of variouscriteria.

Sign in / Sign up

Export Citation Format

Share Document