- 09 Jul 2018
Merge Search for Production Scheduling in Open Pit Mining
09 Jul 2018 - 5:30 pm - 6:30 pm
Open pit mine planning requires the solution of very large optimisation problems. The instances are typically far too large for exact methods and finding good heuristic solutions is challenging. In this paper we discuss one such mine planning problem, the precedence constrained production scheduling problem (PCPSP). Matheuristics tackle such problems by using the machinery of mathematical programming in a heuristic framework. In this talk we focus on a new matheuristic that combines features from many different solutions, making it particularly suited for parallel or distributed computing approaches where we want to gain an advantage from multiple optimisation processes running in parallel. We describe the problem, matheuristic algorithm and provide empirical evidence of its computational effectiveness.
Andreas Ernst is a Professor of Operations Research in the School of Mathematics at Monash University. He has over 20 years experience in the development of optimisation and simulation models to assist businesses in Australia with strategic and operational decision making. He is the director of MAXIMA, the Monash Academy for Cross & Interdisciplinary Mathematical Applications. His research interests focus on scheduling and optimisation for large scale industrial applications, including high performance combinatorial optimisation algorithms, parallel matheuristics and network optimisation.
Technical University of Munich
TUM School of Management