The subject is a part of the study program in Chemical Engineering. The tenure track position offers the appointee to the assistant/associate professorship an opportunity to obtain a tenured position and advancement p a full professorship, i.e. the highest level of the tenure track system.

The field of activity of the position is process technology, which especially includes technical aspects of chemical unit operations, their construction, dimensioning and instrumentation, as well as energy and environmental engineering. Emphasis is also placed on process and production planning and production economics. The work task of the appointed person include development of research and education, to raise funding for research, to participate in national and international cooperation and administrative task.

For more information visit this link.

]]>A blog post about the research visit is available here.

Professor Grossmann has received a great number of awards and honors and is one of the most cited authors in computer science and chemical engineering. He was included in the distinguished group “One hundred engineers of the modern era”, selected by the American Institute of Chemical Engineers (AIChE) in 2008. Professor Grossmann also received an honorary doctorate from Åbo Akademi University in 2002. Professor Grossmann is a member of the International Scientific Panel of the OSE group and was the plenary speaker at the annual OSE seminar in 2011.

]]>Prof. Westerlund was invited by Prof. Montaz Ali, a member of the International Scientific Panel of the OSE group, to hold a guest lecture titled: “Aspects on Solving Convex and Nonconvex Mixed Integer Nonlinear Programming Problems”. The presentation file is available here.

]]>Introduction:

Optimization is an important activity in decision making, in analyzing and in improving production in a factory. In mathematical terms, an optimization problem is the problem of finding the best solution out of all feasible solutions. An optimization problem consists of an objective function, variables and constraints. The objective function is a mathematical function expressing what we want to maximize or minimize. For example, in manufacturing we may want to maximize the profits or minimize the cost of production. The variables can express how much resources are needed or the time spent in various production steps. Binary variables can be decision variables expressing whether a factory should be built at a location or not. The constraints are functions that define the boundaries for the variables, e.g. the amount of resources used cannot exceed the available resources.

In order to solve a problem to optimality, the problem often needs to be convex, that means that a local minimum is also the global one. If the problem is not convex it can be convexified. In this thesis, we work with quadratic problems and in order to obtain a convex problem the quadratic matrix needs to be positive-semidefinite, that is that all eigenvalues of the matrix are in the positive half-space of the complex plane. If the optimal solution cannot be obtained we can still obtain indications on how good the solution is with a upper bound (UB) and a lower bound (LB). A upper bound is a solution that fulfills all constraints and is therefore a feasible solution. The lower bound is a relaxed solution where some of the constraints may not be active. When the upper and the lower bound are alike, the problem is solved to optimality.

A linear program (LP) is a problem formulation including only continuous variables and linear constraints. When introducing integer variables, the problem goes from LP to mixed integer linear programming (MILP). If there are quadratic terms in the objective function, the problem is called quadratic program (QP) and if there are as well quadratic constraints, it is a quadratically constrained quadratic program (QCQP). One can use heuristic methods in order to obtain good solutions in a short amount of time. However, the solution is neither guaranteed to be the optimal solution, nor can any bounds for the solution be obtained.

]]>The GOW’16 conference was organized at the University of Minho, Campus de Gualtar, in Braga Portugal September 4-8, 2016.

The following two presentations were held:

- Andreas Lundell — Improvements to the SHOT solver for convex MINLP
- Jan Kronqvist — Lifted Polyhedral Approximations in Convex Mixed Integer Nonlinear Programming

The full proceedings is available here.here

]]>The presentation held was titled “Testing a Non-Diagonal Convex Reformulation Technique for 0-1 Quadratic Programs” and can be viewed here.

]]>The BFG-2015 conference was organized at Imperial College London, UK in June 2015.

Their presentations held by the two speakers from the OSE group can be downloaded here:

]]>Place: Hilbertrummet, ASA building, Åbo Akademi University, Turku, Finland.

Time: 11 March 2015, 3.05 PM.

The abstract can be downloaded here.

]]>Place: Hilbertrummet, ASA building, Åbo Akademi University, Turku, Finland.

Time: 28 January 2015, 3 PM.

Giorgio Ferrari is a post doctoral researcher at the Center for Mathematical Economics, Bielefeld University, Germany.

In this talk we examine a Markovian model for the optimal irreversible investment problem of a firm aiming at minimizing total expected costs of production. We model market uncertainty and the cost of investment per unit of production capacity as two independent one-dimensional regular diffusions, and we consider a general convex running cost function. The optimization problem is set as a three-dimensional degenerate singular stochastic control problem. We provide the optimal control as the solution of a Skorohod reflection problem at a suitable free-boundary surface. Such boundary arises from the analysis of a family of two-dimensional parameter-dependent optimal stopping problems and it is characterized in terms of the family of unique continuous solutions to parameter-dependent nonlinear integral equations of Fredholm type.

]]>Title: Mean-Variance Optimal Stopping for Geometric Lévy Processes

Place: Hilbertrummet, ASA building, Åbo Akademi University, Turku, Finland.

Time: 14 January 2015, 3 PM.

Gad is a PhD student at the University of Copenhagen, Denmark.

An abstract of the talk can be downloaded here.

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