Tony T. Tran

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We study an unrelated parallel machines scheduling problem with sequence and machine dependent setup times. A logicbased Benders decomposition approach is proposed to minimize the makespan. This approach is a hybrid model that makes use of a mixed integer programming master problem and a specialized solver for travelling salesman subproblems. The master(More)
The microbial quality of five types of fresh produce obtained at the retail level was determined by standard quantitative techniques. These techniques included aerobic plate count (APC), total coliform counts, Escherichia coli counts, and yeast and mold counts. Three different methods were used to determine total coliform counts, which consisted of(More)
We study the unrelated parallel machine scheduling problem with sequence and machine dependent setup times and the objective of makespan minimization. Two exact decomposition-based methods are proposed based on logic-based Benders decomposition and branch-and-check. These approaches are hybrid models that make use of a mixed integer programming master(More)
Bacterial detection in foods by nucleic acid probes is limited by microflora competition during selective enrichment. Probe target concentration by extraction and fractionation of enrichments may diminish this limitation. The 1-h AccuProbe chemiluminescent culture identification test for Listeria monocytogenes was used as a model. Its high detection(More)
Stability analysis consists of identifying conditions under which the number of jobs in a system is guaranteed to remain bounded over time. To date, such longrun performance guarantees have not been available for periodic approaches to dynamic scheduling problems. However, stability has been extensively studied in queueing theory. In this paper, we(More)
Dynamic scheduling problems consist of both challenging combinatorics, as found in classical scheduling problems, and stochastics due to uncertainty about the arrival times, resource requirements, and processing times of jobs. To address these two challenges, we investigate the integration of queueing theory and scheduling. The former reasons about long-run(More)
We investigate the use of optimization-based techniques to model and solve two real-world single robot task planning problems. In the first problem, a robot must plan a set of tasks, each with different temporal constraints. In the second problem, a socially interacting robot must plan a set of tasks while considering the schedules of multiple human users,(More)
Classically, scheduling research in artificial intelligence has concentrated on the combinatorial challenges arising in a large, static domain where the set of jobs, resource capacities, and other problem parameters are known with certainty and do not change. In contrast, queueing theory has focused primarily on the stochastic arrival and resource(More)
Some people like to try cosmetics before purchasing them. With repeated use by different customers, however, the tester kits provided by many retail outlets can become potential vectors of microbial pathogens. A survey was conducted to assess the health risk from bacteria found on shared-use cosmetics. A total of 3027 shared-use cosmetic product samples(More)
An effective approach to solving complex problems is to decompose them and integrate dedicated solvers for those subproblems. We introduce a hybrid decomposition that incorporates: (1) a quantum annealer that samples from the configuration space of a relaxed problem to obtain strong candidate solutions, and (2) a classical processor that maintains a global(More)