A note on scheduling on a single processor with speed dependent on a number of executed jobs
Information Processing Letters
Some scheduling problems with general position-dependent and time-dependent learning effects
Information Sciences: an International Journal
Solution algorithms for the makespan minimization problem with the general learning model
Computers and Industrial Engineering
Single-machine and flowshop scheduling with a general learning effect model
Computers and Industrial Engineering
Some single-machine and m-machine flowshop scheduling problems with learning considerations
Information Sciences: an International Journal
Experience-based approach to scheduling problems with the learning effect
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Computers and Industrial Engineering
A simulated annealing approach to minimize the maximum lateness on uniform parallel machines
Mathematical and Computer Modelling: An International Journal
| Hi-index | 0.00 |
In many situations, a worker's ability improves as a result of repeating the same or similar task; this phenomenon is known as the ''learning effect''. In this paper, the learning effect is considered in a single-machine maximum lateness minimization problem. A branch-and-bound algorithm, incorporating several dominance properties, is provided to derive the optimal solution. In addition, two heuristic algorithms are proposed for this problem. The first one is based on the earliest due date (EDD) rule and a pairwise neighborhood search. The second one is based on the simulated annealing (SA) approach. Our computational results show that the SA algorithm is surprisingly accurate for a small to medium number of jobs. Moreover, the SA algorithm outperforms the traditional heuristic algorithm in terms of quality and execution time for a large number of jobs.