29379871
A Fixed-Length Subset Genetic Algorithm for the p-Median Problem
In this paper, we review some classical recombination operations and devise new heuristic recombinations for the fixed-length subset. Our experimental results on the classical p-median problem indicate that our method is superior and very close to the optimal solution.
16158729
Transshipment Through Crossdocks with Inventory and Time Windows
The supply chain between manufacturers and retailers always includes transshipments through a network of locations. A major challenge in making demand meet supply has been to coordinate transshipment activities across the chain aimed at reducing costs and increasing service levels in the face of a range of factors, including demand fluctuations, short lead times, warehouse limitations and transportation and inventory costs. The success in implementing push-pull strategies, when firms change from one strategy to another in managing the chain and where time lines are crucial, is dependent on adaptive transshipment scheduling. Yet again, in transshipment through crossdocks, where just-in-time objectives prevail, precise scheduling between suppliers, crossdocks and customers is required to avoid inventory backups or delays.
15768911
The Bottleneck Problem with Minimum Quantity Commitments
Given an edge-distance graph of a set of suppliers and clients, the bottleneck problem is to assign each client to a selected supplier minimizing their maximum distance. We introduce minimum quantity commitments to balance workloads of suppliers, provide it a 3-approximation algorithm, and study its generalizations.
8170241
TPBOSCourier: A Transportation Procurement System (for the Procurement of Courier Services)
TPBOSCourier is the Transportation Procurement and Bid Optimization System (TPBOS) for Philips Electronics to automate and optimize its procurement of courier services. It was jointly developed by Red Jasper Limited and the Hong Kong University of Science and Technology, and has been successfully deployed in 2005. Philips typically procures courier services for more than 2500 shipping lanes annually and the use of the software has resulted in significant cost and time savings in analyzing and optimizing procurement decisions. This paper explains the development and design of the TPBOSCourier.
15852916
Induced uncertain linguistic OWA operators applied to group decision making
The ordered weighted averaging (OWA) operator was developed by Yager [IEEE Trans. Syst., Man, Cybernet. 18 (1998) 183]. Later, Yager and Filev [IEEE Trans. Syst., Man, Cybernet.--Part B 29 (1999) 141] introduced a more general class of OWA operators called the induced ordered weighted averaging (IOWA) operators, which take as their argument pairs, called OWA pairs, in which one component is used to induce an ordering over the second components which are exact numerical values and then aggregated. The aim of this paper is to develop some induced uncertain linguistic OWA (IULOWA) operators, in which the second components are uncertain linguistic variables. Some desirable properties of the IULOWA operators are studied, and then, the IULOWA operators are applied to group decision making with uncertain linguistic information.
16217697
Large-sample performance of blind and Group-blind multiuser detectors: a perturbation perspective
In blind and group-blind multiuser detection, different detectors can be designed using either the sample data covariance matrix directly or its eigencomponents. Due to finite-sample effect in practice, their performance deviates from the corresponding optimum. A perturbation technique is developed rigorously and systematically to analyze those detectors in this work. Subject to the assumption that the first-order perturbation dominates, corresponding results can be applied to a practical system of a given sample size. In particular, performance of the following typical detectors is studied for either flat or estimated multipath channels: direct-matrix-inversion (DMI) blind minimum mean-square error (MMSE) detector, subspace blind MMSE detector, direct zero-forcing (ZF) detector, subspace ZF detector, and group-blind hybrid detector. Simulation examples further verify various analytical results.
1744668
Feature Selection with Particle Swarms
Feature selection is widely used to reduce dimension and remove irrelevant features. In this paper, particle swarm optimization is employed to select feature subset for classification task and train RBF neural network simultaneously. One advantage is that both the number of features and neural network configuration are encoded into particles, and in each iteration of PSO there is no iterative neural network training sub-algorithm. Another is that the fitness function considers three factors: mean squared error between neural network outputs and desired outputs, the complexity of network and the number of features, which guarantees strong generalization ability of RBF network. Furthermore, our approach could select as small-sized feature subset as possible to satisfy high accuracy requirement with rational training time. Experimental results on four datasets show that this method is attractive.
1661848
Efficient constraint processing for location-aware computing
For many applications, such as friend finder, buddy tracking, and location mapping in mobile wireless networks or information sharing and cooperative caching in mobile ad hoc networks, it is often important to be able to identify whether a given set of moving objects is close to each other or close to a given point of demarcation. To achieve this, continuously available location position information of thousands of mobile objects must be correlated against each other to identify whether a fixed set of objects is in a certain proximity relation, which, if satisfied, would be signaled to the objects or any interested party. In this paper, we state this problem, referring to it as the location constraint matching problem and present and evaluate solutions for solving it. We introduce two types of location constraints to model the proximity relations and experimentally validate that our solution scales to the processing of hundreds of thousands of constraints and moving objects.
23206750
A least deviation method to obtain a priority vector of a fuzzy preference relation
Based on the transfer relationship between fuzzy preference relation and multiplicative preference relation, this paper proposes a least deviation method to obtain a priority vector of a fuzzy preference relation and studies its desirable properties. A simple convergent iterative algorithm is given and its practicality is shown by two numerical examples.