Wave algorithms:Optimal database search and catalysis

Grover's database search algorithm, although discovered in the context of quantum computation, can be implemented using any physical system that allows superposition of states. A physical realization of this algorithm is described using coupled simple harmonic oscillators, which can be exactly solved in both classical and quantum domains. Classical wave algorithms are far more stable against decoherence compared to their quantum counterparts. In addition to providing convenient demonstration models, they may have a role in practical situations, such as catalysis.

Optimal sequential wireless relay placement on a random lattice path

Our work is motivated by impromptu (or ``as-you-go'') deployment of wireless relay nodes along a path, a need that arises in many situations. In this paper, the path is modeled as starting at the origin (where there is the data sink, e.g., the control center), and evolving randomly over a lattice in the positive quadrant. A person walks along the path deploying relay nodes as he goes. At each step, the path can, randomly, either continue in the same direction or take a turn, or come to an end, at which point a data source (e.g., a sensor) has to be placed, that will send packets to the data sink. A decision has to be made at each step whether or not to place a wireless relay node. Assuming that the packet generation rate by the source is very low, and simple link-by-link scheduling, we consider the problem of sequential relay placement so as to minimize the expectation of an end-to-end cost metric (a linear combination of the sum of convex hop costs and the number of relays placed). This impromptu relay placement problem is formulated as a total cost Markov decision process. First, we derive the optimal policy in terms of an optimal placement set and show that this set is characterized by a boundary (with respect to the position of the last placed relay) beyond which it is optimal to place the next relay. Next, based on a simpler one-step-look-ahead characterization of the optimal policy, we propose an algorithm which is proved to converge to the optimal placement set in a finite number of steps and which is faster than value iteration. We show by simulations that the distance threshold based heuristic, usually assumed in the literature, is close to the optimal, provided that the threshold distance is carefully chosen. (C) 2014 Elsevier B.V. All rights reserved.

Optimal Route Search with the Coverage of Users' Preferences

The preferences of users are important in route search and planning. For example, when a user plans a trip within a city, their preferences can be expressed as keywords shopping mall, restaurant, and museum, with weights 0.5, 0.4, and 0.1, respectively. The resulting route should best satisfy their weighted preferences. In this paper, we take into account the weighted user preferences in route search, and present a keyword coverage problem, which finds an optimal route from a source location to a target location such that the keyword coverage is optimized and that the budget score satisfies a specified constraint. We prove that this problem is NP-hard. To solve this complex problem, we pro- pose an optimal route search based on an A* variant for which we have defined an admissible heuristic function. The experiments conducted on real-world datasets demonstrate both the efficiency and accu- racy of our proposed algorithms.

An optimal sequential procedure for a buying-selling problem with independent observations

We consider a buying-selling problem when two stops of a sequence of independent random variables are required. An optimal stopping rule and the value of a game are obtained.

Are consumers fooled by discounts? An experimental test in a consumer search environment

In this article, we investigate experimentally whether people search optimally and how price promotions influence search behaviour. We implement a sequential search task with exogenous price dispersion in a baseline treatment and introduce discounts in two experimental treatments. We find that search behaviour is roughly consistent with optimal search but also observe some discount biases. If subjects do not know in advance where discounts are offered, the purchase probability is increased by 19 percentage points in shops with discounts, even after controlling for the benefit of the discount and for risk preferences. If consumers know in advance where discounts are given, then the bias is only weakly significant and much smaller (7 percentage points).

Self Assessment-Based Decision Making for Multiagent Cooperative Search

This paper addresses a search problem with multiple limited capability search agents in a partially connected dynamical networked environment under different information structures. A self assessment-based decision-making scheme for multiple agents is proposed that uses a modified negotiation scheme with low communication overheads. The scheme has attractive features of fast decision-making and scalability to large number of agents without increasing the complexity of the algorithm. Two models of the self assessment schemes are developed to study the effect of increase in information exchange during decision-making. Some analytical results on the maximum number of self assessment cycles, effect of increasing communication range, completeness of the algorithm, lower bound and upper bound on the search time are also obtained. The performance of the various self assessment schemes in terms of total uncertainty reduction in the search region, using different information structures is studied. It is shown that the communication requirement for self assessment scheme is almost half of the negotiation schemes and its performance is close to the optimal solution. Comparisons with different sequential search schemes are also carried out. Note to Practitioners-In the futuristic military and civilian applications such as search and rescue, surveillance, patrol, oil spill, etc., a swarm of UAVs can be deployed to carry out the mission for information collection. These UAVs have limited sensor and communication ranges. In order to enhance the performance of the mission and to complete the mission quickly, cooperation between UAVs is important. Designing cooperative search strategies for multiple UAVs with these constraints is a difficult task. Apart from this, another requirement in the hostile territory is to minimize communication while making decisions. This adds further complexity to the decision-making algorithms. In this paper, a self-assessment-based decision-making scheme, for multiple UAVs performing a search mission, is proposed. The agents make their decisions based on the information acquired through their sensors and by cooperation with neighbors. The complexity of the decision-making scheme is very low. It can arrive at decisions fast with low communication overheads, while accommodating various information structures used for increasing the fidelity of the uncertainty maps. Theoretical results proving completeness of the algorithm and the lower and upper bounds on the search time are also provided.

Optimal unemployment insurance for couples

This work analyzes the optimal design of an unemployment insurance program for couples, whose joint search problem in the labor market differ significantly from the problem faced by single agents. We use a version of the sequential search model of the labor market adapted to married agents to compare optimal constant policies for single and married agents, as well as characterize the optimal constant policy when the agency faces single and married agents simultaneously. Our main result is that an agency that gives equal weights to single and married agents will want to give equal utility promises to both types of agents and spend more on the single agent.

Optimal foraging strategies: Lévy walks balance searching and patch exploitation under a very broad range of conditions

While evidence for optimal random search patterns, known as Lévy walks, in empirical movement data is mounting for a growing list of taxa spanning motile cells to humans, there is still much debate concerning the theoretical generality of Lévy walk optimisation. Here, using a new and robust simulation environment, we investigate in the most detailed study to date (24×10(6) simulations) the foraging and search efficiencies of 2-D Lévy walks with a range of exponents, target resource distributions and several competing models. We find strong and comprehensive support for the predictions of the Lévy flight foraging hypothesis and in particular for the optimality of inverse square distributions of move step-lengths across a much broader range of resource densities and distributions than previously realised. Further support for the evolutionary advantage of Lévy walk movement patterns is provided by an investigation into the 'feast and famine' effect, with Lévy foragers in heterogeneous environments experiencing fewer long 'famines' than other types of searchers. Therefore overall, optimal Lévy foraging results in more predictable resources in unpredictable environments.

Simultaneous feature selection and feature weighting using Hybrid Tabu Search/K-nearest neighbor classifier

Feature selection and feature weighting are useful techniques for improving the classification accuracy of K-nearest-neighbor (K-NN) rule. The term feature selection refers to algorithms that select the best subset of the input feature set. In feature weighting, each feature is multiplied by a weight value proportional to the ability of the feature to distinguish pattern classes. In this paper, a novel hybrid approach is proposed for simultaneous feature selection and feature weighting of K-NN rule based on Tabu Search (TS) heuristic. The proposed TS heuristic in combination with K-NN classifier is compared with several classifiers on various available data sets. The results have indicated a significant improvement in the performance in classification accuracy. The proposed TS heuristic is also compared with various feature selection algorithms. Experiments performed revealed that the proposed hybrid TS heuristic is superior to both simple TS and sequential search algorithms. We also present results for the classification of prostate cancer using multispectral images, an important problem in biomedicine.

Vibration analysis of a printed circuit board

The reliability of the printed circuit board assembly under dynamic environments, such as those found onboard airplanes, ships and land vehicles is receiving more attention. This research analyses the dynamic characteristics of the printed circuit board (PCB) supported by edge retainers and plug-in connectors. By modelling the wedge retainer and connector as providing simply supported boundary condition with appropriate rotational spring stiffnesses along their respective edges with the aid of finite element codes, accurate natural frequencies for the board against experimental natural frequencies are obtained. For a PCB supported by two opposite wedge retainers and a plug-in connector and with its remaining edge free of any restraint, it is found that these real supports behave somewhere between the simply supported and clamped boundary conditions and provide a percentage fixity of 39.5% more than the classical simply supported case. By using an eigensensitivity method, the rotational stiffnesses representing the boundary supports of the PCB can be updated effectively and is capable of representing the dynamics of the PCB accurately. The result shows that the percentage error in the fundamental frequency of the PCB finite element model is substantially reduced from 22.3% to 1.3%. The procedure demonstrated the effectiveness of using only the vibration test frequencies as reference data when the mode shapes of the original untuned model are almost identical to the referenced modes/experimental data. When using only modal frequencies in model improvement, the analysis is very much simplified. Furthermore, the time taken to obtain the experimental data will be substantially reduced as the experimental mode shapes are not required.In addition, this thesis advocates a relatively simple method in determining the support locations for maximising the fundamental frequency of vibrating structures. The technique is simple and does not require any optimisation or sequential search algorithm in the analysis. The key to the procedure is to position the necessary supports at positions so as to eliminate the lower modes from the original configuration. This is accomplished by introducing point supports along the nodal lines of the highest possible mode from the original configuration, so that all the other lower modes are eliminated by the introduction of the new or extra supports to the structure. It also proposes inspecting the average driving point residues along the nodal lines of vibrating plates to find the optimal locations of the supports. Numerical examples are provided to demonstrate its validity. By applying to the PCB supported on its three sides by two wedge retainers and a connector, it is found that a single point constraint that would yield maximum fundamental frequency is located at the mid-point of the nodal line, namely, node 39. This point support has the effect of increasing the structure's fundamental frequency from 68.4 Hz to 146.9 Hz, or 115% higher.

Contracting for infrastructure projects as credence goods

Large infrastructure projects are a major responsibility of urban and regional governments, who usually lack expertise to fully specify the demanded projects. Contractors, typically experts on such projects due to experience with similar projects elsewhere, advise of the needed design in their bids. Producing the right design is nevertheless costly. We model such infrastructure projects taking into account their credence goods feature and the costly design effort they require and examine the performance of commonly used contracting methods. We show that when building costs are homogeneous and public information, multi-stage competitive bidding involving shortlisting of two contractors and contingent compensation of both contractors on design efforts outperforms sequential search and the traditional Design-and-Build approach. If building costs are private information of the contractors and are revealed to them after design cost is sunk, sequential search may be superior to the other two methods.