S. Raghavan

The vehicle routing problem : latest advances and new challenges

Overviews and Surveys.- Routing a Heterogeneous Fleet of Vehicles.- A Decade of Capacitated Arc Routing.- Inventory Routing.- The Period Vehicle Routing Problem and its Extensions.- The Split Delivery Vehicle Routing Problem: A Survey.- Challenges and Advances in A Priori Routing.- Metaheuristics for the Vehicle Routing Problem and Its Extensions: A Categorized Bibliography.- Parallel Solution Methods for Vehicle Routing Problems.- Recent Developments in Dynamic Vehicle Routing Systems.- New Directions in Modeling and Algorithms.- Online Vehicle Routing Problems: A Survey.- Modeling and Solving the Capacitated Vehicle Routing Problem on Trees.- Using a Genetic Algorithm to Solve the Generalized Orienteering Problem.- An Integer Linear Programming Local Search for Capacitated Vehicle Routing Problems.- Robust Branch-Cut-and-Price Algorithms for Vehicle Routing Problems.- Recent Models and Algorithms for One-to-One Pickup and Delivery Problems.- One-to-Many-to-One Single Vehicle Pickup and Delivery Problems.- Challenges and Opportunities in Attended Home Delivery.- Chvatal-Gomory Rank-1 Cuts Used in a Dantzig-Wolfe Decomposition of the Vehicle Routing Problem with Time Windows.- Vehicle Routing Problems with Inter-Tour Resource Constraints.- From Single-Objective to Multi-Objective Vehicle Routing Problems: Motivations, Case Studies, and Methods.- Practical Applications.- Vehicle Routing for Small Package Delivery and Pickup Services.- Advances in Meter Reading: Heuristic Solution of the Close Enough Traveling Salesman Problem over a Street Network.- Multiperiod Planning and Routing on a Rolling Horizon for Field Force Optimization Logistics.- Health Care Logistics, Emergency Preparedness, and Disaster Relief: New Challenges for Routing Problems with a Focus on the Austrian Situation.- Vehicle Routing Problems and Container Terminal Operations - An Update of Research.

Fair Payments for Efficient Allocations in Public Sector Combinatorial Auctions

Motivated by the increasing use of auctions by government agencies, we consider the problem of fairly pricing public goods in a combinatorial auction. A well-known problem with the incentive-compatible Vickrey-Clarke-Groves (VCG) auction mechanism is that the resulting prices may not be in the core. Loosely speaking, this means the payments of the winners could be so low, that there are bidders who would have been willing to pay more than the payments of the winning bidders. Clearly, this “unfair” outcome is unacceptable for a public sector auction. Recent advances in auction theory suggest that combinatorial auctions resulting in efficient outcomes and bidder-Pareto-optimal core payments offer a viable practical alternative to address this problem. This paper confronts two critical issues facing the bidder-Pareto-optimal core payment. First, motivated to minimize a bidders ability to benefit through strategic manipulation (through collusive agreement or unilateral action), we demonstrate the strength of a mechanism that minimizes total payments among all such auction outcomes, narrowing the previously broad solution concept. Second, we address the computational difficulties of achieving these outcomes with a constraint-generation approach, promising to broaden the range of applications for which bidder-Pareto-optimal core pricing achieves a comfortably rapid solution.

The Landscape of Electronic Market Design

This paper presents an introductory survey for this special issue of Management Science on electronic markets. We acquaint the reader with some fundamental concepts in the study of electronic market mechanisms, while simultaneously presenting a survey and summary of the essential literature in this area. Along the way, we position each of the papers presented in this special issue within the existing literature, demonstrating the deep impact of these 14 articles on an already broad body of knowledge.

Tabu Search for a Network Loading Problem with Multiple Facilities

This paper examines a network design problem that arises in the telecommunications industry. In this problem, communication between a gateway vertex and a number of demand vertices is achieved through a network of fiber optic cables. Since each cable has an associated capacity (bandwidth), enough capacity must be installed on the links of the network to satisfy the demand, using possibly different types of cables. Starting with a network with no capacity or some capacity already installed, a tabu search heuristic is designed to find a solution that minimizes the cost of installing any additional capacity on the network. This tabu search applies a k-shortest path algorithm to find alternative paths from the gateway to the demand vertices. Numerical results are presented on different types of networks with up to 200 vertices and 100 demand vertices.

Heuristic Search for the Generalized Minimum Spanning Tree Problem

The generalized minimum spanning tree (GMST) problem occurs in telecommunications network planning, where a network of node clusters needs to be connected via a tree architecture using exactly one node per cluster. The problem is known to be NP-hard, and even finding a constant factor approximation algorithm is NP-hard. In this paper, we present two heuristic search approaches for the GMST problem: local search and a genetic algorithm. Our computational experiments show that these heuristics rapidly provide high-quality solutions for the GMST and outperform some previously suggested heuristics for the problem. In our computational tests on 211 test problems (including 169 problems from the TSPLIB set), our local-search heuristic found the optimal solution in 179 instances and our genetic-algorithm procedure found the optimal solution in 185 instances (out of the 211 instances, the optimal solution is known in 187 instances). Further, on each of the 19 unsolved instances from TSPLIB, both our local-search heuristic and genetic-algorithm procedure improved upon the best previously known solution.

The Generalized Covering Salesman Problem

Given a graph G = (N, E), the covering salesman problem (CSP) is to identify the minimum length tour “covering” all the nodes. More specifically, it seeks the minimum-length tour visiting a subset of the nodes in N such that each node i not on the tour is within a predetermined distance di of a node on the tour. In this paper, we define and develop a generalized version of the CSP, and we refer to it as the generalized covering salesman problem (GCSP). Here, each node i needs to be covered at least ki times, and there is a cost associated with visiting each node. We seek a minimum-cost tour such that each node i is covered at least ki times by the tour. We define three variants of the GCSP. In the first case, each node can be visited by the tour at most once. In the second case, visiting a node i more than once is possible, but an overnight stay is not allowed (i.e., to revisit a node i, the tour has to visit another node before it can return to i). Finally, in the third case, the tour can visit each node more than once consecutively. In this paper, we develop two local search heuristics to find high-quality solutions to the three GCSP variants. To test the proposed algorithms, we generated data sets based on traveling salesman problem library instances. Because the CSP and the generalized traveling salesman problem are special cases of the GCSP, we tested our heuristics on both of those problems as well. Overall, the results show that our proposed heuristics find high-quality solutions very rapidly.

Telecommunications Network Design and Management

Preface. 1. Modelling Feasible Network Configurations for UMTS A. Eisenblatter, et al. 2. Omni-directional Cell Planning R.M. Whitaker, S. Hurley. 3. Optimal Design of Wireless Ad-hoc Networks Shin-yi Wu, G. Anandalingam. 4. Survivable Network Design: Routing of Flows and Slacks D. Rajan, A. Atamturk. 5. Planning Self-healing Ring Capacity Under Demand Uncertainty S. Cosares. 6. An Evolutionary Approach to the Multi-Level Capacitated Minimum Spanning Tree Problem I. Gamvros, et al. 7. Optimized Traffic Load Distribution in MPLS Networks G. Hasslinger, S. Schnitter. 8. Scheduling of a Generalized Switch: Heavy Traffic Regime A.L. Stolyar. 9. Asymptotic Analysis of Rate Adaptive Multimedia Streams S. Weber, G.de Veciana. 10. Numerical Methods for Analyzing Queues with Heavy-tailed Distributions J. Shortle, et al. 11. Provisioning for Bandwidth Sharing and Exchange R.C. Hampshire, et al. 12. Autonomic Admission Control for Networked Information Servers G.A. Paleologo, N. Bambos. 13. PAQM: Pro-Active Queue Management for Internet Congestion Control Seungwan Ryu, C. Rump. 14. A Framework for Dynamic Routing and Feedback Regulation of Packet-switched Networks Yi-Ju Chao, B. Morton. 15. Delay-constrained Multi-ring Construction for Ordered Multipoint-to-multipoint Communications Y. Boujelben, et al. 16. Efficient Bandwidth in Multimedia Distribution Networks with Guaranteed Quality of Service J. Kalvenes, N. Keon.

Dual-Based Local Search for the Connected Facility Location and Related Problems

The connected facility location (ConFL) problem arises in a number of applications that relate to the design of telecommunication networks as well as data distribution and management problems on networks. It combines features of the uncapacitated facility location problem with the Steiner tree problem and is known to be NP-complete. In this setting, we wish to install a set of facilities on a communication network and assign customers to the installed facilities. In addition, the set of selected facilities needs to be connected by a Steiner tree. In this paper, we propose a dual-based local search heuristic that combines dual ascent and local search, which together yield strong lower and upper bounds to the optimal solution. Our procedure is applied to a slightly more general version of the ConFL problem that embraces a family of four different problems---the Steiner tree-star problem, the general Steiner tree-star problem, the ConFL problem, and the rent-or-buy problem---that combine facility location decisions with connectivity requirements. Consequently, our solution methodology successfully applies to all of them. We discuss a wide range of computational experiments that indicate that our heuristic is a very effective procedure that finds high-quality solutions very rapidly.

Diversification for better classification trees

Classification trees are widely used in the data mining community. Typically, trees are constructed to try and maximize their mean classification accuracy. In this paper, we propose an alternative to using the mean accuracy as the performance measure of a tree. We investigate the use of various percentiles (representing the risk aversion of a decision maker) of the distribution of classification accuracy in place of the mean. We develop a genetic algorithm (GA) to build decision trees based on this new criterion. We develop this GA further by explicitly creating diversity in the population by simultaneously considering two fitness criteria within the GA. We show that our bicriterion GA performs quite well, scales up to handle large data sets, and requires a small sample of the original data to build a good decision tree.

A visualization model based on adjacency data

In this paper, we describe a model whose focus is on data visualization. We assume the data are provided in adjacency format, as is frequently the case in practice. As an example, individuals who buy item a are likely to buy or consider buying items b, c, and d, also. We present a simple technique for obtaining distance measures between data points. Armed with the resulting distance matrix, we show how Sammon maps can be used to visualize the data points. An application to the college selection process is discussed in detail.