Digital Commons Network^™

Bi-Objective Optimization For A Single Batch Processing Machine, Leena Omar Ghrayeb

Graduate Research Theses & Dissertations

This research proposes a methodology for solving the problem of scheduling jobs with unequal ready times, unequal processing times, and unequal sizes on a single batch processing machine, with the objectives of minimizing makespan and maximum tardiness. Jobs must be placed into batches and scheduled on the machine such that both objectives are minimized, and machine capacity is not violated. The problem under study can be denoted as 1|p-batch, sj, rj| Cmax,Tmax. Based on a review of relevant literature, this problem has not been considered before.

The problem under study is NP-hard. Consequently, meta-heuristics such as Simulated Annealing (SA) and …

Minimizing Total Number Of Tardy Jobs In Parallel Batch Processing Machines Using Column Generation And Simulated Annealing, Sameer Neupane

Graduate Research Theses & Dissertations

This research considers a scheduling problem where jobs need to be grouped into batches and the batches need to be scheduled on parallel batch processing machines with an objective to minimize the total number of tardy jobs. The jobs are assigned to batches in such a way that machine capacity is not violated. This research considers jobs with unequal ready times, unequal processing times and unequal sizes. The machines are identical in processing capabilities; however, their capacities are different. This research aims to develop effective solution approaches to solve the problem under study. A Mixed Integer Linear Programming (MILP) model …

Sky Surveys Scheduling Using Reinforcement Learning, Andres Felipe Alba Hernandez

Graduate Research Theses & Dissertations

Modern cosmic sky surveys (e.g., CMB S4, DES, LSST) collect a complex diversity of astronomical objects. Each of class of objects presents different requirements for observation time and sensitivity. For determining the best sequence of exposures for mapping the sky systematically, conventional scheduling methods do not optimize the use of survey time and resources. Dynamic sky survey scheduling is an NP-hard problem that has been therefore treated primarily with heuristic methods. We present an alternative scheduling method based on reinforcement learning (RL) that aims to optimize the use of telescope resources for scheduling sky surveys.

We present an exploration of …

Minimizing Total Number Of Tardy Jobs In Two-Stage Flow Shop Using Simulated Annealing And Column Generation, Shashwot Uprety

Graduate Research Theses & Dissertations

This research considers a scheduling problem where jobs need to be grouped in batches and scheduled in a two-stage flow shop with batch processing machines. The jobs are batched in such a way that machine capacity is not violated. The batches are scheduled in such a way to reduce the total number of tardy jobs. The problem under study, denoted as F2 | Batch | ΣUi in scheduling literature, has received less attention. The problem under study is NP-hard. Consequently, commercial solvers used to solve mathematical formulations to find an optimal solution require prohibitively long run times.

In this thesis, …