Modeling Freight Markets for Coal

In this paper we study bulk shipping of coal between the central regions in the world. We compare the performance of cost-minimizing models with a gravity model approach. The main finding in the paper is that cost minimizing models provide relative poor fits to data. A simple one parameter gravity model, however, provides very satisfactory fits to observed behaviour.Bulk freight; cost efficiency; gravity modeling

Searching for optimal integer solutions to set partitioning problems using column generation

We describe a new approach to produce integer feasible columns to a set partitioning problem directly in solving the linear programming (LP) relaxation using column generation. Traditionally, column generation is aimed to solve the LP relaxation as quick as possible without any concern of the integer properties of the columns formed. In our approach we aim to generate the columns forming the optimal integer solution while simultaneously solving the LP relaxation. By this we can remove column generation in the branch and bound search. The basis is a subgradient technique applied to a Lagrangian dual formulation of the set partitioning problem extended with an additional surrogate constraint. This extra constraint is not relaxed and is used to better control the subgradient evaluations. The column generation is then directed, via the multipliers, to construct columns that form feasible integer solutions. Computational experiments show that we can generate the optimal integer columns in a large set of well known test problems as compared to both standard and stabilized column generation and simultaneously keep the number of columns smaller than standard column generation

A maximum entropy approach to the newsvendor problem with partial information

In this paper, we consider the newsvendor model under partial information, i.e., where the demand distribution D is partly unknown. We focus on the classical case where the retailer only knows the expectation and variance of D. The standard approach is then to determine the order quantity using conservative rules such as minimax regret or Scarf's rule. We compute instead the most likely demand distribution in the sense of maximum entropy. We then compare the performance of the maximum entropy approach with minimax regret and Scarf's rule on large samples of randomly drawn demand distributions. We show that the average performance of the maximum entropy approach is considerably better than either alternative, and more surprisingly, that it is in most cases a better hedge against bad results.Newsvendor model; entropy; partial information

Some new bounds for the travelling salesman problem

The Clarke and Wright heuristic for the travelling salesman problem (TSP) has been used for several decades as a tool for finding good solutions for TSP and other vehicle routing problems (VRP). In this paper we offer a simple, but fundamental relationship between the cost of a Hamiltonian cycle measured in the original cost matrix and the cost of the same cycle measured in a saving matrix. This relationship leads to a new and simple lower bound for TSP that some times is better than more traditional bounds based on so-called 1-trees. We also offer some upper bounds for the optimal solution of TSP. Some examples are given in order to illustrate the new bounds and compare these with the classical ones

The coauthorship network analysis of the Norwegian school of economics

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

Centrality Computation in Weighted Networks Based on Edge-Splitting Procedure

The analysis of network’s centralities has a high-level significance for many real-world applications. The variety of game and graph theoretical approaches has a paramount purpose to formalize a relative importance of nodes in networks. In this paper we represent an algorithm for the centrality calculation in the domain of weighted networks. The given algorithm calculates network centralities for weighted graphs based on the proposed procedure of edges’ splitting. The approach is tested and illustrated based on different types of network topologies

The Analysis of Leadership Formation in Networks Based on Shapley Value

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

An analysis of a combinatorial auction

Our objective is to find prices on individual items in a combinatorial auction that support the optimal allocation of bundles of items, i.e. the solution to the winner determination problem of the combinatorial auction. The item-prices should price the winning bundles according to the corresponding winning bids, whereas the bundles that do not belong to the winning set should have strictly positive reduced cost. I.e. the bid on a non-winning bundle is strictly less than the sum of prices of the individual items that belong to the bundle, thus providing information to the bidders why they are not in the winning set. Since the winner determination problem is an integer program, in general we cannot find a linear price-structure with these characteristics. However, in this article we make use of sensitivity analysis and duality in linear programming to obtain this kind of price-information. The ideas are illustrated by means of numerical examples

The Method of Leader’s Overthrow in Networks

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