Minority influence and optimal problem-solving

An analogous thinking task was used to test Nemeth's Convergent–Divergent theory of majority and minority influence. Participants read a (base) problem and one of three solutions (one of which is considered the ‘best' solution). They then generated solutions to a second (target) problem which shared similar structural features to the first problem. Due to the similarities between problems, the solution given to the first problem can be used as an analogy in solving the second. In contrast to Nemeth's theory, when the solution to the base problem was endorsed by a numerical majority there was not an increase in analogy-transfer in solving the target problem. However, in support of Nemeth's theory, when the base solution was supported by a numerical minority then the participants were more likely to generate the ‘best' solution to the target problem regardless of which base solution they were given. Copyright © 1999 John Wiley & Sons, Ltd.

Parallel strategy for optimal learning in perceptrons

We developed a parallel strategy for learning optimally specific realizable rules by perceptrons, in an online learning scenario. Our result is a generalization of the Caticha–Kinouchi (CK) algorithm developed for learning a perceptron with a synaptic vector drawn from a uniform distribution over the N-dimensional sphere, so called the typical case. Our method outperforms the CK algorithm in almost all possible situations, failing only in a denumerable set of cases. The algorithm is optimal in the sense that it saturates Bayesian bounds when it succeeds.

Agent-orientated auction mechanism and strategy design

Agent-based technology is playing an increasingly important role in today’s economy. Usually a multi-agent system is needed to model an economic system such as a market system, in which heterogeneous trading agents interact with each other autonomously. Two questions often need to be answered regarding such systems: 1) How to design an interacting mechanism that facilitates efficient resource allocation among usually self-interested trading agents? 2) How to design an effective strategy in some specific market mechanisms for an agent to maximise its economic returns? For automated market systems, auction is the most popular mechanism to solve resource allocation problems among their participants. However, auction comes in hundreds of different formats, in which some are better than others in terms of not only the allocative efficiency but also other properties e.g., whether it generates high revenue for the auctioneer, whether it induces stable behaviour of the bidders. In addition, different strategies result in very different performance under the same auction rules. With this background, we are inevitably intrigued to investigate auction mechanism and strategy designs for agent-based economics. The international Trading Agent Competition (TAC) Ad Auction (AA) competition provides a very useful platform to develop and test agent strategies in Generalised Second Price auction (GSP). AstonTAC, the runner-up of TAC AA 2009, is a successful advertiser agent designed for GSP-based keyword auction. In particular, AstonTAC generates adaptive bid prices according to the Market-based Value Per Click and selects a set of keyword queries with highest expected profit to bid on to maximise its expected profit under the limit of conversion capacity. Through evaluation experiments, we show that AstonTAC performs well and stably not only in the competition but also across a broad range of environments. The TAC CAT tournament provides an environment for investigating the optimal design of mechanisms for double auction markets. AstonCAT-Plus is the post-tournament version of the specialist developed for CAT 2010. In our experiments, AstonCAT-Plus not only outperforms most specialist agents designed by other institutions but also achieves high allocative efficiencies, transaction success rates and average trader profits. Moreover, we reveal some insights of the CAT: 1) successful markets should maintain a stable and high market share of intra-marginal traders; 2) a specialist’s performance is dependent on the distribution of trading strategies. However, typical double auction models assume trading agents have a fixed trading direction of either buy or sell. With this limitation they cannot directly reflect the fact that traders in financial markets (the most popular application of double auction) decide their trading directions dynamically. To address this issue, we introduce the Bi-directional Double Auction (BDA) market which is populated by two-way traders. Experiments are conducted under both dynamic and static settings of the continuous BDA market. We find that the allocative efficiency of a continuous BDA market mainly comes from rational selection of trading directions. Furthermore, we introduce a high-performance Kernel trading strategy in the BDA market which uses kernel probability density estimator built on historical transaction data to decide optimal order prices. Kernel trading strategy outperforms some popular intelligent double auction trading strategies including ZIP, GD and RE in the continuous BDA market by making the highest profit in static games and obtaining the best wealth in dynamic games.

Optimal input/output reduction in production processes

While conventional Data Envelopment Analysis (DEA) models set targets for each operational unit, this paper considers the problem of input/output reduction in a centralized decision making environment. The purpose of this paper is to develop an approach to input/output reduction problem that typically occurs in organizations with a centralized decision-making environment. This paper shows that DEA can make an important contribution to this problem and discusses how DEA-based model can be used to determine an optimal input/output reduction plan. An application in banking sector with limitation in IT investment shows the usefulness of the proposed method.

Competitive edge through operations management

A view has emerged within manufacturing and service organizations that the operations management function can hold the key to achieving competitive edge. This has recently been emphasized by the demands for greater variety and higher quality which must be set against a background of increasing cost of resources. As nations' trade barriers are progressively lowered and removed, so producers of goods and service products are becoming more exposed to competition that may come from virtually anywhere around the world. To simply survive in this climate many organizations have found it necessary to improve their manufacturing or service delivery systems. To become real ''winners'' some have adopted a strategic approach to operations and completely reviewed and restructured their approach to production system design and operations planning and control. The articles in this issue of the International journal of Operations & Production Management have been selected to illustrate current thinking and practice in relation to this situation. They are all based on papers presented to the Sixth International Conference of the Operations Management Association-UK which was held at Aston University in June 1991. The theme of the conference was "Achieving Competitive Edge" and authors from 15 countries around the world contributed to more than 80 presented papers. Within this special issue five topic areas are addressed with two articles relating to each. The topics are: strategic management of operations; managing change; production system design; production control; and service operations. Under strategic management of operations De Toni, Filippini and Forza propose a conceptual model which considers the performance of an operating system as a source of competitive advantage through the ''operation value chain'' of design, purchasing, production and distribution. Their model is set within the context of the tendency towards globalization. New's article is somewhat in contrast to the more fashionable literature on operations strategy. It challenges the validity of the current idea of ''world-class manufacturing'' and, instead, urges a reconsideration of the view that strategic ''trade-offs'' are necessary to achieve a competitive edge. The importance of managing change has for some time been recognized within the field of organization studies but its relevance in operations management is now being realized. Berger considers the use of "organization design", ''sociotechnical systems'' and change strategies and contrasts these with the more recent idea of the ''dialogue perspective''. A tentative model is suggested to improve the analysis of different strategies in a situation specific context. Neely and Wilson look at an essential prerequisite if change is to be effected in an efficient way, namely product goal congruence. Using a case study as its basis, their article suggests a method of measuring goal congruence as a means of identifying the extent to which key performance criteria relating to quality, time, cost and flexibility are understood within an organization. The two articles on production systems design represent important contributions to the debate on flexible production organization and autonomous group working. Rosander uses the results from cases to test the applicability of ''flow groups'' as the optimal way of organizing batch production. Schuring also examines cases to determine the reasons behind the adoption of ''autonomous work groups'' in The Netherlands and Sweden. Both these contributions help to provide a greater understanding of the production philosophies which have emerged as alternatives to more conventional systems -------for intermittent and continuous production. The production control articles are both concerned with the concepts of ''push'' and ''pull'' which are the two broad approaches to material planning and control. Hirakawa, Hoshino and Katayama have developed a hybrid model, suitable for multistage manufacturing processes, which combines the benefits of both systems. They discuss the theoretical arguments in support of the system and illustrate its performance with numerical studies. Slack and Correa's concern is with the flexibility characteristics of push and pull material planning and control systems. They use the case of two plants using the different systems to compare their performance within a number of predefined flexibility types. The two final contributions on service operations are complementary. The article by Voss really relates to manufacturing but examines the application of service industry concepts within the UK manufacturing sector. His studies in a number of companies support the idea of the ''service factory'' and offer a new perspective for manufacturing. Harvey's contribution by contrast, is concerned with the application of operations management principles in the delivery of professional services. Using the case of social-service provision in Canada, it demonstrates how concepts such as ''just-in-time'' can be used to improve service performance. The ten articles in this special issue of the journal address a wide range of issues and situations. Their common aspect is that, together, they demonstrate the extent to which competitiveness can be improved via the application of operations management concepts and techniques.

A new three phase method (SDP method) for the multi-objective vehicle routing problem with simultaneous delvery and pickup (VRPSDP)

Transportation service operators are witnessing a growing demand for bi-directional movement of goods. Given this, the following thesis considers an extension to the vehicle routing problem (VRP) known as the delivery and pickup transportation problem (DPP), where delivery and pickup demands may occupy the same route. The problem is formulated here as the vehicle routing problem with simultaneous delivery and pickup (VRPSDP), which requires the concurrent service of the demands at the customer location. This formulation provides the greatest opportunity for cost savings for both the service provider and recipient. The aims of this research are to propose a new theoretical design to solve the multi-objective VRPSDP, provide software support for the suggested design and validate the method through a set of experiments. A new real-life based multi-objective VRPSDP is studied here, which requires the minimisation of the often conflicting objectives: operated vehicle fleet size, total routing distance and the maximum variation between route distances (workload variation). The former two objectives are commonly encountered in the domain and the latter is introduced here because it is essential for real-life routing problems. The VRPSDP is defined as a hard combinatorial optimisation problem, therefore an approximation method, Simultaneous Delivery and Pickup method (SDPmethod) is proposed to solve it. The SDPmethod consists of three phases. The first phase constructs a set of diverse partial solutions, where one is expected to form part of the near-optimal solution. The second phase determines assignment possibilities for each sub-problem. The third phase solves the sub-problems using a parallel genetic algorithm. The suggested genetic algorithm is improved by the introduction of a set of tools: genetic operator switching mechanism via diversity thresholds, accuracy analysis tool and a new fitness evaluation mechanism. This three phase method is proposed to address the shortcoming that exists in the domain, where an initial solution is built only then to be completely dismantled and redesigned in the optimisation phase. In addition, a new routing heuristic, RouteAlg, is proposed to solve the VRPSDP sub-problem, the travelling salesman problem with simultaneous delivery and pickup (TSPSDP). The experimental studies are conducted using the well known benchmark Salhi and Nagy (1999) test problems, where the SDPmethod and RouteAlg solutions are compared with the prominent works in the VRPSDP domain. The SDPmethod has demonstrated to be an effective method for solving the multi-objective VRPSDP and the RouteAlg for the TSPSDP.

Optimal design for correlated processes with input-dependent noise

Optimal design for parameter estimation in Gaussian process regression models with input-dependent noise is examined. The motivation stems from the area of computer experiments, where computationally demanding simulators are approximated using Gaussian process emulators to act as statistical surrogates. In the case of stochastic simulators, which produce a random output for a given set of model inputs, repeated evaluations are useful, supporting the use of replicate observations in the experimental design. The findings are also applicable to the wider context of experimental design for Gaussian process regression and kriging. Designs are proposed with the aim of minimising the variance of the Gaussian process parameter estimates. A heteroscedastic Gaussian process model is presented which allows for an experimental design technique based on an extension of Fisher information to heteroscedastic models. It is empirically shown that the error of the approximation of the parameter variance by the inverse of the Fisher information is reduced as the number of replicated points is increased. Through a series of simulation experiments on both synthetic data and a systems biology stochastic simulator, optimal designs with replicate observations are shown to outperform space-filling designs both with and without replicate observations. Guidance is provided on best practice for optimal experimental design for stochastic response models. © 2013 Elsevier Inc. All rights reserved.

Mobile app reading speed test

Aim: To validate the accuracy and repeatability of a mobile app reading speed test compared with the traditional paper version. Method: Twenty-one subjects wearing their full refractive correction glasses read 14 sentences of decreasing print size between 1.0 and -0.1 logMAR, each consisting of 14 words (Radner reading speed test) at 40 cm with a paper-based chart and twice on iPad charts. Time duration was recorded with a stop watch for the paper chart and on the App itself for the mobile chart allowing critical print size (CPS) and optimal reading speed (ORS) to be derived objectively. Results: The ORS was higher for the mobile app charts (194±29 wpm; 195±25 wpm) compared with the paper chart (166±20 wpm; F=57.000, p<0.001). The CPS was lower for the mobile app charts (0.17±0.20 logMAR; 0.18±0.17 logMAR) compared with the paper chart (0.25±0.17 logMAR; F=5.406, p=0.009). The mobile app test had a mean difference repeatability of 0.30±22.5 wpm, r=0.917 for ORS, and a CPS of 0.0±0.2 logMAR, r=0.769. Conclusions: Repeatability of the app reading speed test is as good (ORS) or better (CPS) than previous studies on the paper test. While the results are not interchangeable with paper-based charts, mobile app tablet-based tests of reading speed are reliable and rapid to perform, with the potential to capture functional visual ability in research studies and clinical practice.

Recent Results on Stability Analysis of an Optimal Assembly Line Balance

Two assembly line balancing problems are addressed. The first problem (called SALBP-1) is to minimize number of linearly ordered stations for processing n partially ordered operations V = {1, 2, ..., n} within the fixed cycle time c. The second problem (called SALBP-2) is to minimize cycle time for processing partially ordered operations V on the fixed set of m linearly ordered stations. The processing time ti of each operation i ∈V is known before solving problems SALBP-1 and SALBP-2. However, during the life cycle of the assembly line the values ti are definitely fixed only for the subset of automated operations V\V . Another subset V ⊆ V includes manual operations, for which it is impossible to fix exact processing times during the whole life cycle of the assembly line. If j ∈V , then operation times tj can differ for different cycles of the production process. For the optimal line balance b of the assembly line with operation times t1, t2, ..., tn, we investigate stability of its optimality with respect to possible variations of the processing times tj of the manual operations j ∈ V .

Optimal design of the renewable energy map of Greece using weighted goal-programming and data envelopment analysis

Renewable energy forms have been widely used in the past decades highlighting a "green" shift in energy production. An actual reason behind this turn to renewable energy production is EU directives which set the Union's targets for energy production from renewable sources, greenhouse gas emissions and increase in energy efficiency. All member countries are obligated to apply harmonized legislation and practices and restructure their energy production networks in order to meet EU targets. Towards the fulfillment of 20-20-20 EU targets, in Greece a specific strategy which promotes the construction of large scale Renewable Energy Source plants is promoted. In this paper, we present an optimal design of the Greek renewable energy production network applying a 0-1 Weighted Goal Programming model, considering social, environmental and economic criteria. In the absence of a panel of experts Data Envelopment Analysis (DEA) approach is used in order to filter the best out of the possible network structures, seeking for the maximum technical efficiency. Super-Efficiency DEA model is also used in order to reduce the solutions and find the best out of all the possible. The results showed that in order to achieve maximum efficiency, the social and environmental criteria must be weighted more than the economic ones.

Methods of Regularities Searching Based on Optimal Partitioning

The purpose of discussed optimal valid partitioning (OVP) methods is uncovering of ordinal or continuous explanatory variables effect on outcome variables of different types. The OVP approach is based on searching partitions of explanatory variables space that in the best way separate observations with different levels of outcomes. Partitions of single variables ranges or two-dimensional admissible areas for pairs of variables are searched inside corresponding families. Statistical validity associated with revealed regularities is estimated with the help of permutation test repeating search of optimal partition for each permuted dataset. Method for output regularities selection is discussed that is based on validity evaluating with the help of two types of permutation tests.

Conditional Confidence Interval for the Scale Parameter of a Weibull Distribution

2000 Mathematics Subject Classification: 62F25, 62F03.

On the Optimal Allocations in Economy with Fixed Total Resources

Здравко Д. Славов - В тази статия се разглежда математически модел на икономика с фиксирани общи ресурси, както и краен брой агенти и блага. Обсъжда се ролята на някои предположения за отношенията на предпочитание на икономическите агенти, които влияят на характеристиките на оптимално разпределените дялове. Доказва се, че множеството на оптимално разпределените дялове е свиваемо и притежава свойството на неподвижната точка.

A Variable Neighborhood Search Approach for Solving the Maximum Set Splitting Problem

This paper presents a Variable neighbourhood search (VNS) approach for solving the Maximum Set Splitting Problem (MSSP). The algorithm forms a system of neighborhoods based on changing the component for an increasing number of elements. An efficient local search procedure swaps the components of pairs of elements and yields a relatively short running time. Numerical experiments are performed on the instances known in the literature: minimum hitting set and Steiner triple systems. Computational results show that the proposed VNS achieves all optimal or best known solutions in short times. The experiments indicate that the VNS compares favorably with other methods previously used for solving the MSSP. ACM Computing Classification System (1998): I.2.8.

Comparison of Multivariate and Univariate Models for Genetic Evaluation of Milk Yield based on Test Day Data

2000 Mathematics Subject Classification: 62H12, 62P99