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The traveling salesman problem and its variants are among the most studied problems in the literature on transportation and logistics. In one of these variants known as the profitable tour problem [2], a profit-maximizing carrier decides whether to visit a particular customer with respect to the prize the customer offers for being visited and traveling cost associated with the visit, all in the context of other customers. The purpose of this paper is to define the profitable tour game, a cooperative version of the profitable tour problem, and to derive its properties. We are particularly interested in prize allocations that create incentives for the carrier to visit all relevant customers. Applications of the profitable tour game might include for example situations in shipping where a carrier is able to serve demands of several customers with a single vehicle. Whether it comes to delivery or pickup of goods, the customers might need to induce the carrier to visit them by offering sufficient rewards. Subsequently, negotiation with other customers in the same position could lead to better prizes while the carrier's visit would remain guaranteed. This knowledge could also be utilized by the carrier by offering specifically tailored discounts on multiple orders from the same area or by evaluating and pricing of new customers.

In this paper, we use probabilistic methods to analyze learning effects in a behavioral experiment on the newsvendor model. We argue why we should believe that suggested orders follow a multinomial logit distribution, and use the single parameter in that model to extract information on learning effects. We revisit the data, analyzed previously by Bolton et al. (2012), and show that our model predicts the pull-to-center effect in these experimental data very well.

Methods for leader’s detection and overthrow in networks are useful tools for decision-making in many real-life cases, such as criminal networks with hidden patterns or money laundering networks. In the given research, we represent the algorithms that detect and overthrow the most influential node to the weaker positions following the greedy method in terms of structural modifications. We employed the concept of Shapley value from the area of cooperative games to measure a node’s leadership and used it as the core of the developed leader’s overthrow algorithms. The approaches are illustrated based on the trivial network structures and tested on real-life networks. The results are represented in tabular and graphical formats.

In this paper, we use a reformulation of the symmetric and the asymmetric travelling salesman problem more suitable for Lagrangean relaxation and analyse the new approach on examples from TSP Lib. Furthermore the Lagrangean relaxed subproblems are travelling salesman alike which means that almost all that is known on the travelling salesman polytope can be used when the subproblems are to be solved.

In the given research we study a leadership formation of the most influential nodes in networks. Specifically, we analyze the competition between a leader and a follower based on the Stackelberg leadership model. Applying the concept of Shapley value to measure node’s importance, we represent the mechanism of Shapley-based Stackelberg leadership formation in networks. The approach is tested and represented in tabular and graphical formats.

In the given research we analyse how an agent can move towards leadership in a socio-economic network. For the node’s (i.e., agent’s) importance measure we use the Shapley value (SV) concept from the area of cooperative games. We consider SV as the node’s centrality that corresponds to the significance of the agent within the socio-economic network. Using the polynomial algorithm developed by Aadithya, Ravindran, Michalak, & Jennings (2010) to compute SVs we analyze the way of creating new linkages to increase an agent’s significance (i.e., importance) in networks.

Recently Beltran-Royo et.al presented a Semi-Lagrangean relaxation for the classical p-median location problem. The results obtained using the Semi-Lagrangean relaxation approach were quite impressive. In this paper we use a reformulation of the p-median problem in order to start from a formulation more suitable for Semi-Lagrangean relaxation and analyse the new approach on examples from the OR library.

We construct the coauthorship network based on the scientific collaboration between the faculty members at the Norwegian Business School (BI) and based on their international academic publication experience. The network structure is based on the BI faculties’ publications recognized by the ISI Web of Science for the period 1950 – Spring, 2014. The given network covers the publication activities of the BI faculty members (over eight departments) based on the information retrieved from the ISI Web of Science in Spring, 2014. In this paper we analyse the constructed coauthorship network in different aspects of the theory of social networks analysis.

We construct the coauthorship network based on the scientific collaboration between the faculty members at the Norwegian School of Economics (NHH) and based on their international academic publication experience. The network structure is based on the NHH faculties’ publications recognized by the ISI Web of Science for the period 1950 – Spring, 2014. The given network covers the publication activities of the NHH faculty members (over six departments) based on the information retrieved from the ISI Web of Science in Spring, 2014. In this paper we analyse the constructed coauthorship network in different aspects of the theory of social networks analysis.