Kerem Akartunali

I am Professor of Management Science at Strathclyde Business School, where I joined as John Anderson Research Lecturer in Optimization in 2010, after completing my Ph.D. in 2007 at the University of Wisconsin-Madison and then working as a postdoctoral research fellow in the Department of Mathematics and Statistics at the University of Melbourne. My research interests and expertise are in integer programming, robust and network optimization, and their applications, in particular in lot-sizing/production planning, transportation scheduling/planning, health applications such as radiation treatment planning and nurse rostering, and energy applications such as offshore windfarm installation. My research has been funded by various bodies/organizations including EPSRC, Scottish Funding Council, Capita and US Air Force Office of Scientific Research. I have worked with many organizations, including First Milk, Glasgow City Council, NHS, Scottish Power, Scottish Southern Energy and Technip, in a variety of projects ranging from short-term consultancy to long-term research partnerships.

A Polyhedral Study of Two-Period Relaxations for Big-Bucket Lot-Sizing Problems: Zero Setup Case

  • Kerem Akartunali
  • Mahdi Doostmohammadi
    • Categories Integer Programming, Polyhedra, Production and Logistics

    In this paper, we investigate the two-period subproblems proposed by Akartunal{\i} et al. (2014) for big-bucket lot-sizing problems, which have shown a great potential for obtaining strong bounds for these problems. In particular, we study the polyhedral structure of the mixed integer sets related to two relaxations of these subproblems for the special case of … Read more

    Local Cuts and Two-Period Convex Hull Closures for Big-Bucket Lot-Sizing Problems

  • Kerem Akartunali
  • Ioannis Fragkos
  • Andrew J. Miller
  • Tao Wu
    • Categories Applications - OR and Management Sciences, Integer Programming

    Despite the significant attention they have drawn, big bucket lot-sizing problems remain notoriously difficult to solve. Previous work of Akartunali and Miller (2012) presented results (computational and theoretical) indicating that what makes these problems difficult are the embedded single-machine, single-level, multi-period submodels. We therefore consider the simplest such submodel, a multi-item, two-period capacitated relaxation that … Read more

    A unified mixed-integer programming model for simultaneous fluence weight and aperture optimization in VMAT, Tomotherapy, and Cyberknife

  • Kerem Akartunali
  • Vicky Mak-Hau
  • Thu Tran
    • Categories Biomedical Applications, Integer Programming

    In this paper, we propose and study a unified mixed-integer programming model that simultaneously optimizes fluence weights and multi-leaf collimator (MLC) apertures in the treatment planning optimization of VMAT, Tomotherapy, and CyberKnife. The contribution of our model is threefold: i. Our model optimizes the fluence and MLC apertures simultaneously for a given set of control … Read more

    A Computational Analysis of Lower Bounds for Big Bucket Production Planning Problems

  • Kerem Akartunali
  • Andrew J. Miller
    • Categories Production and Logistics Tags , , ,

    In this paper, we analyze a variety of approaches to obtain lower bounds for multi-level production planning problems with big bucket capacities, i.e., problems in which multiple items compete for the same resources. We give an extensive survey of both known and new methods, and also establish relationships between some of these methods that, to … Read more

    A Heuristic Approach for Big Bucket Production Planning Problems

  • Kerem Akartunali
  • Andrew J. Miller
    • Categories Production and Logistics Tags , , , ,

    Multi-level production planning problems in which multiple items compete for the same resources frequently occur in practice, yet remain daunting in their difficulty to solve. In this paper we propose a heuristic framework that can generate high quality feasible solutions quickly for various kinds of lot-sizing problems. In addition, unlike many other heuristics, it generates … Read more