A variable neighborhood search algorithm for the constrained task allocation problem

A Variable Neighborhood Search algorithm is proposed for solving a task allocation problem whose main characteristics are: (i) each task requires a certain amount of resources and each processor has a finite capacity to be search between task it is assigned; (ii) the cost of solutions includes fixed cost when using processors, assigning cost and communication cost between task assigned to different processors. A computational experiment shows that the algorithm is satisfactory in terms of time and solution qualit

Mining whole sample mass spectrometry proteomics data for biomarkers: an overview

In this paper we aim to provide a concise overview of designing and conducting an MS proteomics experiment in such a way as to allow statistical analysis that may lead to the discovery of novel biomarkers. We provide a summary of the various stages that make up such an experiment, highlighting the need for experimental goals to be decided upon in advance. We discuss issues in experimental design at the sample collection stage, and good practise for standardising protocols within the proteomics laboratory. We then describe approaches to the data mining stage of the experiment, including the processing steps that transform a raw mass spectrum into a useable form. We propose a permutation-based procedure for determining the significance of reported error rates. Finally, because of its general advantages in speed and cost, we suggest that MS proteomics may be a good candidate for an early primary screening approach to disease diagnosis, identifying areas of risk and making referrals for more specific tests without necessarily making a diagnosis in its own right. Our discussion is illustrated with examples drawn from experiments on bovine blood serum conducted in the Centre for Proteomic Research (CPR) at Southampton University

Coordination of production scheduling and vehicle routing problem with release and due date

This work is concerned with solving the vehicle routing problem (VRP) which takes into account the customer’s release and due date. The problem studied can also be categorized as a non-classical VRP as the departure times of vehicles depend on the dates of orders released from the production line and become available for the distribution process. The problem is investigated through two stages. In the first stage, vehicle routing problem with release and due date (VRPRDD) is treated. At the beginning of the planning, it is assumed that the dates where the customer orders become available are known. A mathematical formulation is developed to represent the problem which solved by several heuristics, i.e. Variable Neighborhood Search (VNS), Large Neighborhood Search (LNS) and Tabu Search (TS). The algorithms are written in C++ and run on a PC computer with an Intel PentiumCore by using 56’s Solomon instances with some modification. Different kinds of vehicle routing problem have been tackled in order to see the performance of proposed heuristics. The results are then compared in order to find the best method which yields the least routing cost solution. From the outcome obtained, VNS is proved to be the best algorithm which generates the least cost solution to our problem. Further investigation has been carried out in stage two which considers the extension of VRPRDD. The coordination of production sequence and vehicle routing (PS-VRPRDD) is the main subject to our problem studied in which the best production sequence will leads to the least routing. Classical decomposition approach, namely Alternateis used which decompose the problems into two sub-problems, i.e. production sequence and vehicle routing. The results proved that effective coordination shows the large potential savings that attract the interest of industrial distributors in optimizing their distribution process in practice

Train Scheduling and Rescheduling in the UK with a Modified Shifting Bottleneck Procedure

This paper introduces a modified shifting bottleneck approach to solve train scheduling and rescheduling problems. The problem is formulated as a job shop scheduling model and a mixed integer linear programming model is also presented. The shifting bottleneck procedure is a well-established heuristic method for obtaining solutions to the job shop and other machine scheduling problems. We modify the classical shifting bottleneck approach to make it suitable for the types of job shop problem that arises in train scheduling. The method decomposes the problem into several single machine problems. Different variations of the method are considered with regard to solving the single machine problems. We compare and report the performance of the algorithms for a case study based on part of the UK railway network

Flexible Model Interpretability through Natural Language Model Editing

Model interpretability and model editing are crucial goals in the age of large language models. Interestingly, there exists a link between these two goals: if a method is able to systematically edit model behavior with regard to a human concept of interest, this editor method can help make internal representations more interpretable by pointing towards relevant representations and systematically manipulating them.Comment: Extended Abstract -- work in progress. BlackboxNLP202

The Economics of Crypto-Democracy

Democracy is an economic problem of choice constrained by transaction costs and information costs. Society must choose between competing institutional frameworks for the conduct of voting and elections. These decisions are constrained by the technologies and institutions available. Blockchains are a governance technology that reduces the costs of consensus, coordinating information, and monitoring and enforcing contracts. Blockchain could be applied to the voting and electoral process to form a crypto-democracy. Analysed through the Institutional Possibility Frontier framework, we propose that blockchain lowers disorder and dictatorship costs of the voting and electoral process. In addition to efficiency gains, this technological progress has implications for decentralised institutions of voting. One application of crypto-democracy, quadratic voting, is discussed

Moving epidemic method (MEM) applied to virology data as a novel real time tool to predict peak in seasonal influenza healthcare utilisation. The Scottish experience of the 2017/18 season to date

Scotland observed an unusual influenza A(H3N2)- dominated 2017/18 influenza season with healthcare services under significant pressure. We report the application of the moving epidemic method (MEM) to virology data as a tool to predict the influenza peak activity period and peak week of swab positivity in the current season. This novel MEM application has been successful locally and is believed to be of potential use to other countries for healthcare planning and building wider community resilience

Integrated crop pollination to buffer spatial and temporal variability in pollinator activity

Insect pollination improves the yield and quality of many crops, yet there is increasing evidence of insufficient insect pollinators limiting crop production. Effective Integrated Crop Pollination (ICP) involves adaptable, targeted and cost effective management of crop pollination and encourages the use of both wild and managed pollinators where appropriate. In this study we investigate how the addition of honeybee hives affects the community of insects visiting oilseed rape, and if hive number and location affect pollinator foraging and oilseed rape pollination in order to provide evidence for effective ICP. We found that introducing hives increased overall flower visitor numbers and altered the pollinator community, which became dominated by honeybees. Furthermore a greater number of hives did not increase bee numbers significantly but did result in honeybees foraging further into fields. The timing of surveys and proximity to the field edge influenced different pollinators in different ways and represents an example of spatial and temporal complementarity. For example dipteran flower visitor numbers declined away from the field edge whereas honeybees peaked at intermediate distances into the field. Furthermore, no significant effects of survey round on wild bees overall was observed but honeybee numbers were relatively lower during peak flowering and dipteran abundance was greater in later survey rounds. Thus combining diverse wild pollinators and managed species for crop pollination buffers spatial and temporal variation in flower visitation. However we found no effect of insect pollination on seed set or yield of oilseed rape in our trial, highlighting the critical need to understand crop demand for insect pollination before investments are made in managing pollination services

CAW-coref: Conjunction-Aware Word-level Coreference Resolution

State-of-the-art coreference resolutions systems depend on multiple LLM calls per document and are thus prohibitively expensive for many use cases (e.g., information extraction with large corpora). The leading word-level coreference system (WL-coref) attains 96.6% of these SOTA systems' performance while being much more efficient. In this work, we identify a routine yet important failure case of WL-coref: dealing with conjoined mentions such as 'Tom and Mary'. We offer a simple yet effective solution that improves the performance on the OntoNotes test set by 0.9% F1, shrinking the gap between efficient word-level coreference resolution and expensive SOTA approaches by 34.6%. Our Conjunction-Aware Word-level coreference model (CAW-coref) and code is available at https://github.com/KarelDO/wl-coref.Comment: Accepted at CRAC 202