Computing and Information Systems - Research Publications
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ItemNo Preview AvailableA Decomposition-Based Algorithm for the Scheduling of Open-Pit Networks over Multiple Time Periods(INFORMS (Institute for Operations Research and Management Sciences), 2016)We consider the multiple-time-period, short-term production scheduling problem for a network of multiple open-pit mines and ports. Ore produced at each mine, in each period, is transported by rail to a set of ports and blended into products for shipping. Each port forms these blends to a specification, as stipulated in contracts with downstream customers. This problem belongs to a class of multiple producer/consumer scheduling problems in which producers are able to generate a range of products, a combination of which are required by consumers to meet specified demands. In practice, short-term schedules are formed independently at each mine, tasked with achieving a grade and quality target outlined in a medium-term plan. Because of uncertainty in the data available to a medium-term planner and the dynamics of the mining environment, such targets may not be feasible in the short term. In this paper, we present an algorithm in which the grade and quality targets assigned to each mine are iteratively adapted, ensuring the satisfaction of blending constraints at each port while generating schedules for each mine that maximise resource utilisation. This paper was accepted by Yinyu Ye, optimization.
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ItemNo Preview AvailableMulti-objective short-term production scheduling for open-pit mines: a hierarchical decomposition-based algorithm(TAYLOR & FRANCIS LTD, 2018-12-02)This article presents a novel algorithm for solving a short-term open-pit production-scheduling problem in which several objectives, of varying priority, characterize the quality of each solution. A popular approach employs receding horizon control, dividing the horizon into N period-aggregates of increasing size (number of periods or span). An N-period mixed integer program (MIP) is solved for each period in the original horizon to incrementally construct a production schedule one period at a time. This article presents a new algorithm that, in contrast, decomposes the horizon into N period-aggregates of equal size. Given a schedule for these N periods, obtained by solving an N-period MIP, the first of these aggregates is itself decomposed into an N-period scheduling problem with guidance provided on what regions of the mine should be extracted. The performance of this hierarchical decomposition-based approach is compared with that of receding horizon control on a suite of data sets generated from an operating mine producing millions of tons of ore annually. As the number of objectives being optimized increases, the hierarchical decomposition-based algorithm outperforms receding horizon control, in a majority of instances.
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ItemNo Preview AvailableShort-term planning for open pit mines: a review(TAYLOR & FRANCIS LTD, 2019-07-04)This review examines the current state-of-the-art in short-term planning for open-pit mines, with a granularity that spans days, weeks or months, and a horizon of less than one to two years. In the academic literature, the short-term planning problem for open-pit mines has not been as widely considered as that for the medium- and long-term horizons. We highlight the differences between short- and longer term planning in terms of both the level of detail to which a mine site is modelled, and the objectives that are optimised when making decisions. We summarise the range of techniques that have been developed for generating short-term plans, capturing both mathematical programming-based methods and heuristic approaches using local-search and decomposition. We identify key challenges and future directions in which to advance the state-of-the-art in short-term planning for open-pit mines.
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ItemExplaining circuit propagation(SPRINGER, 2014-01)
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ItemSearch combinators(SPRINGER, 2013-04)
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ItemSolving RCPSP/max by lazy clause generation(SPRINGER, 2013-06)
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ItemSymmetries, almost symmetries, and lazy clause generation(SPRINGER, 2014-10)
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ItemThe future of optimization technology(SPRINGER, 2014-04)
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ItemSynthesizing Optimal Switching Lattices(Association for Computing Machinery, 2014-11)The use of nanoscale technologies to create electronic devices has revived interest in the use of regular structures for defining complex logic functions. One such structure is the switching lattice, a two-dimensional lattice of four-terminal switches. We show how to directly construct switching lattices of polynomial size from arbitrary logic functions; we also show how to synthesize minimal-sized lattices by translating the problem to the satisfiability problem for a restricted class of quantified Boolean formulas. The synthesis method is an anytime algorithm that uses modern SAT solving technology and dichotomic search. It improves considerably on an earlier proposal for creating switching lattices for arbitrary logic functions.
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ItemDiscovery and analysis of consistent active subnetworks in cancers(BMC, 2013-01-21)Gene expression profiles can show significant changes when genetically diseased cells are compared with non-diseased cells. Biological networks are often used to identify active subnetworks (ASNs) of the diseases from the expression profiles to understand the reason behind the observed changes. Current methodologies for discovering ASNs mostly use undirected PPI networks and node centric approaches. This can limit their ability to find the meaningful ASNs when using integrated networks having comprehensive information than the traditional protein-protein interaction networks. Using appropriate scoring functions to assess both genes and their interactions may allow the discovery of better ASNs. In this paper, we present CASNet, which aims to identify better ASNs using (i) integrated interaction networks (mixed graphs), (ii) directions of regulations of genes, and (iii) combined node and edge scores. We simplify and extend previous methodologies to incorporate edge evaluations and lessen their sensitivity to significance thresholds. We formulate our objective functions using mixed integer programming (MIP) and show that optimal solutions may be obtained. We compare the ASNs obtained by CASNet and similar other approaches to show that CASNet can often discover more meaningful and stable regulatory ASNs. Our analysis of a breast cancer dataset finds that the positive feedback loops across 7 genes, AR, ESR1, MYC, E2F2, PGR, BCL2 and CCND1 are conserved across the basal/triple negative subtypes in multiple datasets that could potentially explain the aggressive nature of this cancer subtype. Furthermore, comparison of the basal subtype of breast cancer and the mesenchymal subtype of glioblastoma ASNs shows that an ASN in the vicinity of IL6 is conserved across the two subtypes. This result suggests that subtypes of different cancers can show molecular similarities indicating that the therapeutic approaches in different types of cancers may be shared.