Scheduling on a two-machine flowshop subject to random breakdowns with a makespan objective function (original) (raw)
1995, European Journal of Operational Research
Sign up for access to the world's latest research.
checkGet notified about relevant papers
checkSave papers to use in your research
checkJoin the discussion with peers
checkTrack your impact
Related papers
Dual criteria scheduling on a two-machine flowshop subject to random breakdowns
International Transactions in Operational Research, 1998
Decision makers often consider multiple objectives when making scheduling decisions. However, very little research has been done in multiple machine environments with multiple objectives. Furthermore, only a couple of researchers considered¯owshops with machine breakdowns while, in reality, machines are subject to random breakdowns. We consider a two-machine¯owshop scheduling problem, where machines suer random breakdowns and processing times are constant, with respect to both makespan and maximum lateness objective functions. We provide an elimination criterion in a two-machine¯owshop when both machines are subject to random breakdowns. We show that the longest processing time and the shortest processing time orders are optimal with respect to both criteria in a two-machine ordered¯owshop when the ®rst or the second machine, respectively, suers stochastic breakdowns.
Scheduling a two-stage flowshop under makespan constraint
Mathematical and Computer …, 2006
We consider selecting and sequencing jobs in a two stage flowshop so that the selected jobs are completed before a specified time limit (such as the end of a shift). The objective is to maximize the weighted (reward) sum of the selected jobs. We show that the problem is NP-hard, and present two procedures to find an optimum solution. The first procedure uses dynamic programming, and the second uses mixed integer programming. The integer programming formulation exploits special properties of the problem and solves large instances of the problem. We also develop heuristics and provide worst case performance guarantees. An improvement procedure is also developed. Extensive computational testing shows that our heuristics, when used jointly with the improvement procedure, yield excellent results (providing solutions within 3% of the optimum in an average sense) for both balanced and unbalanced shops.
Loading Preview
Sorry, preview is currently unavailable. You can download the paper by clicking the button above.