Kjetil K. Haugen

Progressive hedging as a meta-heuristic applied to stochastic lot-sizing

Abstract In a great many situations, the data for optimization problems cannot be known with certainty and furthermore the decision process will take place in multiple time stages as the uncertainties are resolved. This gives rise to a need for stochastic programming (SP) methods that create solutions that are hedged against future uncertainty. The progressive hedging algorithm (PHA) of Rockafellar and Wets is a general method for SP. We cast the PHA in a meta-heuristic framework with the sub-problems generated for each scenario solved heuristically. Rather than using an approximate search algorithm for the exact problem as is typically the case in the meta-heuristic literature, we use an algorithm for sub-problems that is exact in its usual context but serves as a heuristic for our meta-heuristic. Computational results reported for stochastic lot-sizing problems demonstrate that the method is effective.

Omya Hustadmarmor Optimizes Its Supply Chain for Delivering Calcium Carbonate Slurry to European Paper Manufacturers

The Norwegian company Omya Hustadmarmor supplies calcium carbonate slurry to European paper manufacturers from a single processing plant, using chemical tank ships of various sizes to transport its products. Transportation costs are lower for large ships than for small ships, but their use increases planning complexity and creates problems in production. In 2001, the company faced overwhelming operational challenges and sought operations-research-based planning support. The CEO, Sturla Steinsvik, contacted More Research Molde, which conducted a project that led to the development of a decision-support system (DSS) for maritime inventory routing. The core of the DSS is an optimization model that is solved through a metaheuristic-based algorithm. The system helps planners to make stronger, faster decisions and has increased predictability and flexibility throughout the supply chain. It has saved production and transportation costs close to US

The profit maximizing capacitated lot-size (PCLSP) problem

7 million a year. We project additional direct savings of nearly US

European club football: why enormous revenues are not enough?

4 million a year as the company adds even larger ships to the fleet as a result of the project. In addition, the company has avoided investments of US

Solving Large-scale Profit Maximization Capacitated Lot-size Problems by Heuristic Methods

35 million by increasing capacity utilization. Finally, the project has had a positive environmental effect by reducing overall oil consumption by more than 10 percent.

The financial crisis in European football - a game theoretic approach.

This paper extends the results for capacitated lot-sizing research to include pricing. Based on a few examples, the new version appears to by much easier to solve computationally. The paper, by including price, can modify demand as well as production schedule. Due to model assumptions (form of demand) a feasible solution can be found easily, unlike CLSP.

The multi-player performance-enhancing drug game.

This essay discusses why many European football clubs have experienced financial problems, despite earning high revenues. The fact that European football clubs are win maximizers make them more aggressive when competing for talented players than professional teams on other continents. So-called eyes of a needle, such as promotion, (avoiding) relegation and qualifying for international tournaments strengthen the cost push effects. Due to the free movement of labour, any regulations have to be implemented simultaneously across the whole of Europe. Achieving such unilateral agreement in 52 national leagues is difficult. European football has a history of powerful clubs that are not favourable to regulations that can reduce their advantages. A game-theory approach illustrates the mechanisms that lead European clubs to spend more resources than they can afford. Additionally, this part offers a new and hopefully interesting explanation, besides objective function differences, when it comes to understanding micro differences between US and European sports.

Stochastic programming: Potential hazards when random variables reflect market interaction

This paper introduces a simple heuristic for a quadratic programming sub-problem within a Lagrangean relaxation heuristic for a dynamic pricing and lot-size problem. This simple heuristic is demonstrated to work well on both ‘standard problem instances’ from the CLSP-literature, as well as on very large-scale cases. Additionally, we introduce price constraints within the framework of dynamic pricing, discuss their relevance in a real world market modelling, and demonstrate their applicability within this algorithmic framework.

The new Norwegian incentive system for publication: from bad to worse

Abstract This paper proposes an alternative view of classical sports economic labour market theory. Through simple direct game theory, we are able to show explanations other than the traditional marginal or average revenue equality equilibrium models of Quirk and El-Hodiri (1971). For instance, the choice of objective is important, however not vital. We build our approach directly on preliminary research by Solberg and Haugen (2010) and extend their relatively simple modelling and conclusions. Particularly, we focus on the claimed economic crisis of European football and propose more complex explanatory patterns than objective function choice for observed financial differences between US sports and European football.

Large-Scale Joint Price-Inventory Decision Problems, Under Resource Limitation and a Discrete Price Set

This paper extends classical work on economics of doping into a multi-player game setting. Apart from being among the first papers formally formulating and analysing a multi-player doping situation, we find interesting results related to different types of Nash-equilibria (NE). Based mainly on analytic results, we claim at least two different NE structures linked to the choice of prize functions. Linear prize functions provide NEs characterised by either everyone or nobody taking drugs, while non-linear prize functions lead to qualitatively different NEs with significantly more complex predictive characteristics.