Michelle L. Blom

A Decomposition-Based Algorithm for the Scheduling of Open-Pit Networks Over Multiple Time Periods

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.

An analysis of New South Wales electronic vote counting

We re-examine the 2012 local government elections in New South Wales, Australia. The count was conducted electronically using a randomised form of the Single Transferable Vote (STV). It was already well known that randomness does make a difference to outcomes in some seats. We describe how the process could be amended to include a demonstration that the randomness was chosen fairly. Second, and more significantly, we found an error in the official counting software, which caused a mistake in the count in the council of Griffith, where candidate Rina Mercuri narrowly missed out on a seat. We believe the software error incorrectly decreased Mercuris winning probability to about 10%---according to our count she should have won with 91% probability. The NSW Electoral Commission (NSWEC) corrected their code when we pointed out the error, and made their own announcement. We have since investigated the 2016 local government election (held after correcting the error above) and found two new errors. We notified the NSWEC about these errors a few days after they posted the results.

Short-term scheduling of an open-pit mine with multiple objectives

ABSTRACT This article presents a novel algorithm for the generation of multiple short-term production schedules for an open-pit mine, in which several objectives, of varying priority, characterize the quality of each solution. A short-term schedule selects regions of a mine site, known as ‘blocks’, to be extracted in each week of a planning horizon (typically spanning 13 weeks). Existing tools for constructing these schedules use greedy heuristics, with little optimization. To construct a single schedule in which infrastructure is sufficiently utilized, with production grades consistently close to a desired target, a planner must often run these heuristics many times, adjusting parameters after each iteration. A planners intuition and experience can evaluate the relative quality and mineability of different schedules in a way that is difficult to automate. Of interest to a short-term planner is the generation of multiple schedules, extracting available ore and waste in varying sequences, which can then be manually compared. This article presents a tool in which multiple, diverse, short-term schedules are constructed, meeting a range of common objectives without the need for iterative parameter adjustment.

A Decomposition-Based Heuristic for Collaborative Scheduling in a Network of Open-Pit Mines

We consider the short-term production scheduling problem for a network of multiple open-pit mines and ports. Ore produced at each mine is transported by rail to a set of ports and blended into signature products for shipping. Consistency in the grade and quality of production over time is critical for customer satisfaction, whereas the maximal production of blended products is required to maximise profit. In practice, short-term schedules are formed independently at each mine, tasked with achieving the grade and quality targets outlined in a medium-term plan. However, 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. We present a decomposition-based heuristic for this short-term scheduling problem in which the grade and quality goals assigned to each mine are collaboratively adapted---ensuring the satisfaction of blending constraints at each port and exploiting opportunities to maximise production in the network that would otherwise be missed.

Computing the Margin of Victory in Preferential Parliamentary Elections

We show how to use automated computation of election margins to assess the number of votes that would need to change in order to alter a parliamentary outcome for single-member preferential electorates. In the context of increasing automation of Australian electoral processes, and accusations of deliberate interference in elections in Europe and the USA, this work forms the basis of a rigorous statistical audit of the parliamentary election outcome. Our example is the New South Wales Legislative Council election of 2015, but the same process could be used for any similar parliament for which data was available, such as the Australian House of Representatives given the proposed automatic scanning of ballots.

Inventory routing for defense: Moving supplies in adversarial and partially observable environments

Future defense logistics will be heavily reliant on autonomous vehicles for the transportation of supplies. We consider a dynamic logistics problem in which: multiple supply item types are transported between suppliers and consuming (sink) locations; and autonomous vehicles (road-, sea-, and air-based) make decisions on where to collect and deliver supplies in a decentralized manner. Sink nodes consume dynamically varying demands (whose timing and size are not known a priori). Network arcs, and vehicles, experience failures at times, and for durations, that are not known a priori. These dynamic events are caused by an adversary, seeking to disrupt the network. We design domain-dependent planning algorithms for these vehicles whose primary objective is to minimize the likelihood of stockout events (where insufficient resource is present at a sink to meet demand). Cost minimization is a secondary objective. The performance of these algorithms, across varying scenarios, with and without restrictions on communication between vehicles and network locations, is evaluated using agent-based simulation. We show that stockpiling-based strategies, where quantities of resource are amassed at strategic locations, are most effective on large land-based networks with multiple supply item types, with simpler “shuttling”-based approaches being sufficient otherwise.

Short-term planning for open pit mines: a review

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.