Operations Research, Systems Engineering and Industrial Engineering Commons^™

Simulated Annealing Heuristics For The Dynamic Generalized Quadratic Assignment Problem, Yugesh Dhungel

Graduate Theses, Dissertations, and Problem Reports

The Dynamic Generalized Quadratic Assignment Problem (DGQAP) is the task of assigning a set of facilities to a set of locations in a multi-period planning horizon such that the sum of the transportation and assignment/reassignment costs is minimized. The facilities may have different space requirements, and the capacities of locations may vary during the multiple-period planning horizon. Also, multiple facilities may be assigned to each location without violating the space capacity of the location. This research presents a formulation and applications of DGQAP in various layout and assignment problems encountered in the literature. Two Simulated Annealing (SA) metaheuristics named SA …

Metaheuristics For The Generalized Quadratic Assignment Problem, Roseline Mostafa

Graduate Theses, Dissertations, and Problem Reports

The generalized quadratic assignment problem (GQAP) is the task of assigning a set of facilities to a set of locations such that the sum of the assignment and transportation costs is minimized. The facilities may have different space requirements, and the locations may have varying space capacities. Also, multiple facilities may be assigned to each location such that space capacity is not exceeded. In this research, an application of the GQAP is presented for assigning a set of machines to a set of locations on the plant floor. Two meta-heuristics are proposed for solving the GQAP: tabu search (TS) and …

Pharmaceutical Scheduling Using Simulated Annealing And Steepest Descent Method, Bryant Jamison Spencer

Graduate Theses, Dissertations, and Problem Reports

In the pharmaceutical manufacturing world, a deadline could be the difference between losing a multimillion-dollar contract or extending it. This, among many other reasons, is why good scheduling methods are vital. This problem report addresses Flexible Flowshop (FF) scheduling using Simulated Annealing (SA) in conjunction with the Steepest Descent heuristic (SD).

FF is a generalized version of the flowshop problem, where each product goes through S number of stages, where each stage has M number of machines. As opposed to a normal flowshop problem, all ‘jobs’ do not have to flow in the same sequence from stage to stage. The …