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 AvailableSequencing operator counts(AAAI Press, 2016-01-01)Copyright 2016 AAAI, all rights reserved.). Operator-counting is a recently developed framework for analysing and integrating many state-ofthe- art heuristics for planning using Linear Programming. In cost-optimal planning only the objective value of these heuristics is traditionally used to guide the search. However the primal solution, i.e. the operator counts, contains useful information. We exploit this information using a SATbased approach which given an operator-count, either finds a valid plan; or generates a generalized landmark constraint violated by that count. We show that these generalized landmarks can be used to encode the perfect heuristic, h∗, as a Mixed Integer Program. Our most interesting experimental result is that finding or refuting a sequence for an operator-count is most often empirically efficient, enabling a novel and promising approach to planning based on Logic-Based Benders Decomposition (LBBD). This paper originally appeared at ICAPS 2015 and is reproduced with the permission of the Association for Artificial Intelligence ([Davies et al., 2015]
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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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ItemAbstract Interpretation over Non-Lattice Abstract Domains(Springer, 2013)The classical theoretical framework for static analysis of programs is abstract interpretation. Much of the power and elegance of that framework rests on the assumption that an abstract domain is a lattice. Nonetheless, and for good reason, the literature on program analysis provides many examples of non-lattice domains, including non-convex numeric domains. The lack of domain structure, however, has negative consequences, both for the precision of program analysis and for the termination of standard Kleene iteration. In this paper we explore these consequences and present general remedies.
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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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