Minimizing maximum lateness with job families

Article Abstract:

Research is presented concerning the scheduling of jobs on a single machine in a way which provides an optimal solution procedure. The establishment of job families and the minimization of maximum lateness are discussed.

Methods

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Comparison of neural and heuristic methods for a timetabling problem

Article Abstract:

The performances of an annealed neural network, a graph coloring heuristic and a pricing out heuristic in solving a timetabling problem known as the interview scheduling problem were compared. Specifically, the nonparametric statistics were employed to evaluate the solutions delivered by the heuristics and the neural network in terms of quality and execution time. The results showed that heuristics are more effective than neural networks because the latter require multiple repetitions.

Computer networks, Case studies, Evaluation, Neural networks, Heuristic programming

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Stochastically minimizing total flowtime in flowshops with no waiting space

Article Abstract:

A study was conducted to analyze the problem of scheduling jobs with the total flowtime performance measure in two-machine flowshops supporting constant and known processing times. Results indicated that the shortest processing time based on the processing time of the jobs on the first machine stochastically reduced the performance criteria provided that it supports a faster counting process than the second machine. Findings also showed that the shortest processing time based on the processing times of the jobs on the second machine reduced the total flowtime stochastically.

Manufacturing processes, Manufacturing, Stochastic processes

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