Theses and Dissertations

Issuing Body

Mississippi State University


Eksioglu, D. Sandra

Committee Member

Greenwood, G. Allen

Committee Member

Eksioglu, Burak

Date of Degree


Document Type

Graduate Thesis - Open Access


Industrial Engineering

Degree Name

Master of Science (M.S.)


James Worth Bagley College of Engineering


Department of Industrial and Systems Engineering


This study provides heuristic approaches, including an ant colony optimization (ACO) inspired heuristic, to solve a crane scheduling problem that exists in most shipyards, where cranes are a primary means of processing and handling materials. Cranes move on a network of tracks, thus, blocking of crane movements is an issue. The crane scheduling problem consists of two major sub-problems: scheduling problem that determines the best overall order in which jobs are to be performed; the assignment problem that assigns cranes to jobs. The proposed heuristic consists of an Earliest Due Date sorting procedure in combination with an ACO assignment procedure that aims to satisfy the objectives of minimizing makespan while maximizing crane utilization. Test data sets of various sizes are generated and the results of the proposed approach are compared to other developed heuristics. The proposed approach outperforms others in both objective measures and obtains solutions in a timely manner.