Beam search heuristics for quadratic earliness and tardiness scheduling

In this paper, we present beam search heuristics for the single machine scheduling problem with quadratic earliness and tardiness costs, and no machine idle time. These heuristics include classic beam search procedures, as well as filtered and recovering algorithms. We consider three dispatching heuristics as evaluation functions, in order to analyse the effect of different rules on the performance of the beam search procedures. The computational results show that using better dispatching heuristics improves the effectiveness of the beam search algorithms. The performance of the several heuristics is similar for instances with low variability. For high variability instances, however, the detailed, filtered and recovering beam search procedures clearly outperform the best existing heuristic. The detailed beam search algorithm performs quite well, and is recommended for small to medium size instances. For larger instances, however, this procedure requires excessive computation times, and the recovering beam search algorithm then becomes the heuristic of choice.scheduling, heuristics, beam search, single machine, quadratic earliness, quadratic tardiness

Greedy randomized dispatching heuristics for the single machine scheduling problem with quadratic earliness and tardiness penalties

In this paper, we present greedy randomized dispatching heuristics for the single machine scheduling problem with quadratic earliness and tardiness costs, and no machine idle time. The several heuristic versions differ, on the one hand, on the strategies involved in the construction of the greedy randomized schedules. On the other hand, these versions also differ on whether they employ only a final improvement step, or perform a local search after each greedy randomized construction. The proposed heuristics were compared with existing procedures, as well as with optimum solutions for some instance sizes. The computational results show that the proposed procedures clearly outperform their underlying dispatching heuristic, and the best of these procedures provide results that are quite close to the optimum. The best of the proposed algorithms is the new recommended heuristic for large instances, as well as a suitable alternative to the best existing procedure for the larger of the middle size instances.scheduling, single machine, early/tardy, quadratic penalties, greedy randomized dispatching rules

Logistic system design of an underground freight pipeline system

"July 2014."Dissertation Supervisor: Dr. James Noble.Includes vita.Underground Freight Pipeline (UFP) systems utilize the underground space in metro areas that is otherwise not utilized for freight transportation. Two fundamental logistics issues in the design of a UFP system are network configuration and capsule control. This research develops two capsule control models that minimize total tardiness squared of cargo delivery and associated heuristic algorithms to solve large-scale problems. Two network design models are introduced that minimizes both operational and construction cost of UFP system. The UFP network design Comprehensive Model can only be solved to optimality for small sized problem. To reduce the computational complexity, the UFP network design Two Step Model that is able to generate high quality network design solutions is developed. Then, a case study of a UFP network design in Greater New York area is presented.Includes bibliographical references (pages 159-162)