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Title: Some problems in sequencing and scheduling utilizing branch and bound algorithms

Thesis/Dissertation ·
OSTI ID:5564061

This dissertation deals with branch and bound algorithms which are applied to the two-machine flow-shop problem with sparse precedence constraints and the optimal sequencing and scheduling of multiple feedstocks in a batch-type digester problem. The problem studied here is to find a schedule which minimizes the maximum flow time with the requirement that the schedule does not violate a set of sparse precedence constraints. This research provides a branch and bound algorithm which employs a lower bounding rule and is based on an adjustment of the sequence obtained by applying Johnson's algorithm. It is demonstrated that this lower bounding procedure in conjunction with Kurisu's branching rule is effective for the sparse precedence constraints problem case. Biomass to methane production systems have the potential of supplying 25% of the national gas demand. The optimal operation of a batch digester system requires the sequencing and scheduling of all batches from multiple feedstocks during a fixed time horizon. A significant characteristic of these systems is that the feedstock decays in storage before use in the digester system. The operational problem is to determine the time to allocate to each batch of several feedstocks and then sequence the individual batches so as to maximize biogas production for a single batch type digester over a fixed planning horizon. This research provides a branch and bound algorithm for sequencing and a two-step hierarchical dynamic programming procedure for time allocation scheduling. An efficient heuristic algorithm is developed for large problems and demonstrated to yield excellent results.

Research Organization:
Texas A and M Univ., College Station, TX (USA)
OSTI ID:
5564061
Resource Relation:
Other Information: Thesis (Ph. D.)
Country of Publication:
United States
Language:
English