Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.
Scheduling methods applied to flowshop                    production systems                                              ...
that provides us with the knowledge in classic                                                             scheduling meth...
Upcoming SlideShare
Loading in …5

Scheduling methods applied to flowshop production systems


Published on

Published in: Technology, Education
  • Be the first to comment

  • Be the first to like this

Scheduling methods applied to flowshop production systems

  1. 1. Scheduling methods applied to flowshop production systems José Fragozo Dept. Of Industrial Engineering, Universidad Del Norte Barranquilla, COLOMBIA Nowadays technology increases in an world the majority of situations are not as simple asexponential rate that is only overcome by our that, in this paper we are going to review the paper “Aambition of keep growing, there are some Weight-Based Multiobjective Genetic Algorithm formultinational companies that manage more money Flowshop Scheduling” published by Zhimin Fangthan some little countries, geographic borders are where develop as the name says a Multiobjectivebeing replaced with economic borders, the whole Genetic Algorithm for Flowshop Schedulingplanet is globalized markets, to be in the (WBMOGA).competition companies need to plan, control andprogram the operations including obviously II. AWEIGHT-BASED MULTIOBJECTIVEproduction that is the vertebral column of the GENETIC ALGORITHM FORsupply chain, logical algorithms are good tools FLOWSHOP SCHEDULINGwhen a scheduling is necessary but are not the Big companies that manage thousands of references,bests, there are too many ways to set up a hundreds of clients and hundreds of vendors withproductive system and logical algorithms are different features can deal with more than oneoptimal for only specific setups. problem at the same time, multiobjetive algorithms, this heuristic algorithm in particular start searching for all the possible solutions, let’s review the example I. INTRODUCTION that appear on the paper, there is flowshop problem with 20 jobs and 10 machines, the information is onFlowshop scheduling is one of the most well-known the next table.scheduling problems. Since Johnson´s work, thatcreate and algorithm that has his name and works tominimize the makespan and is optimal for 2 machinessetup, various scheduling criteria have beenconsidered, the some of the most well-known aremakespan, maximum tardiness, maximum flowtimeand total flowtime. Some researchers extended single-objective flowshop scheduling problems tomultiobjective problems. Logical algorithms onlytake in account one objective, and in a lot of simplesituations works perfectly, however in industrial
  2. 2. that provides us with the knowledge in classic scheduling methods and always emphasized us to investigate in the new methods. V. REFERENCES [1] Zhimin Fang;, "A Weight-Based Multiobjective Genetic Algorithm for Flowshop Scheduling," Artificial Intelligence and Computational Intelligence, 2009. AICI 09. International Conference on , vol.1, no., pp.373-377, 7-8 Nov. 2009 doi: 10.1109/AICI.2009.130 Table1.The algorithm in this case will stop once evaluate48600 possible solutions, algorithm start comparingpairs of solutions, and start trying with the all possiblecombinations, if a solution dominate the other isbetter, and is saving the best options, once it finishonly the 10 better options are the potential solutionsand the it choose the best one. III. CONCLUSIONSScheduling methods needs to be applied according tothe situation´s complexity, classic methods are goodbackgrounds when a scheduling its required howeverare not optimal in all scenarios, even can give uswrong solutions in some cases, scheduling is apowerful tool to ordinate works in a company in orderto raise the objective, or like in this case theobjectives with this multiobjetives algorithm,heuristic algorithms require tools like powerfulcomputers that maybe will be a significant investmentbut the results compensates the investment, that issure, a scheduled company is a competitive companythat has a perfect equilibrium with the vendors, theclients and itself. IV. ACKNOWLEDGMENTSThis paper was supported by “Universidad DelNorte”, Ing. Daniel Romero and Ing. Carlos Paternina