Reflections about pseudo-dual prices in combinatorial auctions

Combinatorial auctions permitting bids on bundles of items have been developed to remedy the exposure problem associated with single-item auctions. Given winning bundle prices a set of item prices is called market clearing or equilibrium if all the winning (losing) bids are greater (less) than or equal to the total price of the bundle items. However, the prices for individual items are not readily computed once the winner determination problem is solved. This is due to the duality gap of integer programming caused by the indivisibility of the items. In this paper we reflect on the calculation of approximate or pseudo-dual item prices. In particular, we present a novel scheme based on the aggregation of winning bids. Our analysis is illustrated by means of numerical examples

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

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

Mixed contracts for the newsvendor problem with real options

In this paper we consider the newsvendor model with real options. We consider a mixed contract where the retailer can order a combination of q units subject to the conditions in a classical newsvendor contract and Q real options on the same items. We provide a closed form solution to this mixed contract when the demand is discrete and study some of its properties. We also offer an explicit solution for the continuous case. In particular we demonstrate that a mixed contract may be superior to a real option contract when a manufacturer has a bound on how much variance she is willing to accept.Newsvendor model; real options; discrete demand; mixed contract

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 comparative analysis of the NHH and BI networks

Based on the co-authorship networks of the Norwegian School of Economics (NHH) and the BI Norwegian Business School we present a comparative analysis in terms of structures, collaborations and publications. The networks’ structures are based on the NHH and the BI faculties’ publications recognized by the ISI Web of Science for the period 1950 – Spring, 2014. The analysed networks cover the publication activities of the NHH and the BI faculty members based on the data retrieved from ISI Web of Science in Spring, 2014

Shapley-Based Stackelberg Leadership Formation in Networks

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

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