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There is a large demand for seasonal crops year-round within Australia, even when they are considered out of season. The demand is satisfied by continually moving production throughout the year to climates where the crops are in season. Management of the supply chain for a major national grower is challenging for several reasons. Due to the large number of planting decisions, it is standard practice for a team of production planners to create the annual production plan. For fresh food production, the supply chain does not contain intermediate storage requiring that the production plan is carefully timed not to waste resources with overproduction. In this paper, we develop a supply chain model that simultaneously manages the production of multiple crops across many growing regions. Production is set to satisfy the demand of multiple end-products while considering the packing plants' throughput capacity, each growing region's harvest capacity, and farm capacity. A time delay may be applied when moving between stages of the supply chain due to the geographic scale being modelled. A deterministic Mixed Integer Program is used to find the optimal planting plan, which minimises the deviation from demand for all products year-round at a minimal cost. Due to the excessive runtime for solving the model, a heuristic solution method is introduced. Numerical experiments demonstrate the advantage of the proposed model over the current manual planning process, which can solve the problem faster and with less deviation across the planning horizon. [ABSTRACT FROM AUTHOR]

Green hydrogen, produced from renewable electricity, can be transported long distances in multiple mediums. In this paper, a Techno-economic model is proposed to show the economic viability of global green hydrogen transport along 15 major regional routes such as Australia to Asia and Europe for the first time. A Monte Carlo-based technique is presented to assess the levelised cost of green hydrogen for different regions for the next 30 years. Depending on the specific route, green hydrogen can be transported in different forms, including ammonia, Liquid Organic Hydrogen Carrier (LOHC), Hydrogen Slush, compressed or liquefied hydrogen, etc. form and using different modes including shipping, truck, train, and pipeline. A linear programming analysis has been conducted for different regions, showing that among the global projected 300Mt of green hydrogen demand in 2050, 85% will need to be transported between regions to achieve the most economically optimal distribution. • Techno-economic analysis of green H 2 export via 15 worldwide regional trade routes. • Export model includes H2 generation, conversion, transport, and carbon prices. • In 2030, North America will be the largest exporter, followed by Australia. • Higher carbon prices allow for rapid growth in the green hydrogen industry. • Shipping is the most likely and cheapest H 2 export mode for distant transport. [ABSTRACT FROM AUTHOR]

Mineral and metallurgical processing are crucial within the mineral value chain. These processes involve several stages wherein comminution is arguably the most important due to its high energy consumption, and its impact on subsequent extractive processes. Several geological properties of the orebody impact the efficiency of mineral processing and extractive metallurgy; scholars have therefore proposed to deal with the uncertain ore feed in terms of grades and rock types, incorporating operational modes that represent different plant configurations that provide coordinated system-wide responses. Even though these studies offer insights into how mine planning impacts the ore fed into the plant, the simultaneous optimization of mine plan and metallurgical plant design has been limited by the existing stochastic mine planning algorithms, which have only limited support for detailing operational modes. The present work offers to fill this gap for open-pit mines through a computationally efficient adaptation of a strategic mine planning algorithm. The adaptation incorporates a linear programming representation of the operational modes which forms a Dantzig-Wolfe decomposition, nested within a high-performing stochastic mine planning algorithm based on a variable neighborhood descent metaheuristic. Sample calculations are presented, loosely based on the Mount Isa deposit in Australia, in which a metallurgical plant upgrade is evaluated, showing that the upgraded design significantly decreases the requirement on the mining equipment, without significantly affecting the NPV. [ABSTRACT FROM AUTHOR]

This article develops a practical framework for the multiobjective optimal planning of a grid-connected renewable-battery system considering a long-period operation. The capacities of wind turbine, solar photovoltaic (PV), and battery storage are optimized by minimizing three objective functions: cost of electricity (COE), grid dependence (GD), and total curtailed energy (TCE). A new rule-based energy management is developed for the long-period operation, where: 1) the capacity degradations of PV and battery are applied; 2) purchase and sell electricity prices are updated for each year using interest and escalation rates; and 3) the salvation value of the components is considered to achieve a realistic economic analysis of the planning problem. The developed multiobjective optimal planning model is examined using the long-period (ten years) real data of wind speed, solar insolation, ambient temperature, and load consumption for a grid-connected household in Australia. It is found that a household with the minimum GD (0.008%) results in a COE of 116 ¢/kWh with a TCE of 100 MWh in ten years. The proposed optimal planning framework based on the long-period operation is compared with the short-period operation. [ABSTRACT FROM AUTHOR]

A challenge for natural area managers is to ensure that public expenditure on land restoration is cost effective, efficient and transparent but this is difficult to achieve in practice, especially when there are many possible projects across multiple years. Here we develop a "roadmap" for investment in land restoration. It explicitly considers space, time and their interaction, in relation to ecological outcomes and restoration costs (and their variation in time and space). Using integer linear programming optimization in a benefit‐cost accounting framework, the roadmap incorporates: transitions between different stages of ecological recovery in a spatial mosaic of multiple ecosystem types; cost schedules associated with managing those transitions over time; time lags between beginning management and achieving outcomes; variations to constraints and goals associated with various factors including site accessibility, specific conservation priorities (such as threatened species or ecosystems); and background environmental trends. This approach enables land managers to: (1) forecast landscape‐scale outcomes of management strategies over long timeframes; (2) address the question of how long it will take and how much it will cost to achieve specific outcomes; and (3) explore potential trade‐offs in outcomes among alternative management strategies. We illustrate its application using a case study of forest restoration in Australia by a local government authority across a public conservation estate comprising 765 land units of varying size, totaling ˜13,000 ha, across five different floristic vegetation types, with an annual budget of ˜AU$5M, projected over a 50‐yr timeframe. These simulations revealed a trade‐off between management strategies that seek to increase either the total cover of native forest or the amount of high quality forest: quality‐based strategies were favored in scenarios in which shorter term (20–30 yr) timeframes were chosen at the outset, but cover‐based strategies were favored if longer time horizons were initially targeted. Projected outcomes were also strongly influenced by assumed background rates of vegetation decline or recovery. Many of the issues in this restoration roadmap are generalizable (even though specific outcomes and trade‐offs are likely to vary among case studies), and the approach is both scalable and transferable to other regions and ecosystems. [ABSTRACT FROM AUTHOR]

A Microsoft Excel workbook, User-Friendly Feed Formulation with Data from Australia (UffdAu.xlsm), has been developed for teaching feed formulation techniques to tertiary level, university students. It runs under both Microsoft Windows and Apple iOS operating systems. The example ingredient composition matrix is based on the Australian Feed Ingredient Database to illustrate the biological and econometric principles of least-cost feed formulation. The nutrient data are based roughly on recent primary breeder company recommendations. The workbook is easily adapted to appropriate ingredients, nutrients, and prices most relevant to the students, wherever it is used. The workbook uses the linear routines of Excel's Solver add-in under the Data heading in the header Ribbon. There is a worksheet illustrating how to adapt non-linear responses such as exogenous enzymes to typical linear models using a step function. Additional worksheets illustrate how proximate analysis can be interpreted in modern analytical chemistry terms and, how various feed energy measures are related to feed composition. UffdAu.xlsm is available free of charge from the Poultry Hub Australia website (https://www.poultryhub.org). [ABSTRACT FROM AUTHOR]

A novel canonical duality theory (CDT) is presented for solving general bilevel mixed integer nonlinear optimization governed by linear and quadratic knapsack problems. It shows that the challenging knapsack problems can be solved analytically in term of their canonical dual solutions. The existence and uniqueness of these analytical solutions are proved. NP-hardness of the knapsack problems is discussed. A powerful CDT algorithm combined with an alternative iteration and a volume reduction method is proposed for solving the NP-hard bilevel knapsack problems. Application is illustrated by benchmark problems in optimal topology design. The performance and novelty of the proposed method are compared with the popular commercial codes. [ABSTRACT FROM AUTHOR]

As residential PV generation penetrates in the low-voltage distribution network (LVDN), the unbalance issue may be intensified due to the asymmetry of generations/loads in different phases. Phase-reconfiguration device (PRD), which can reconfigure connected phases of residential customers, provides an effective method to address this issue. Noting that although the benefit brought by PRDs can vary if they are placed at different locations in the network, little literature has been reported on this topic. To bridge the research gap, this paper presents a novel method to optimally place PRDs in an LVDN aiming at minimizing the power unbalance running through the distribution transformer. The problem considers both installation, operational constraints, and boils down to a challenging mixed-integer non-convex programming problem, which is then reformulated as an efficient solvable mixed-integer linear programming problem. Moreover, operational constraints are relaxed with slack variables penalized in the objective function, which makes sure a feasible solution is always available without or with minimal operational violations. Case studies based on a modified IEEE system and a practical system in Australia demonstrate that an efficient strategy can be provided to address the unbalance issue while improving the network's power supply qualities. [ABSTRACT FROM AUTHOR]

• Presenting a set of mathematical models for green flowshop scheduling problems. • Considering common carbon reduction policies and their corresponding scenarios. • Providing analysis of models and insights to design a framework for green flowshops. • Industries can use our cost-effective strategies to meet limits mandated by government. • Government can explore our integrated framework to gauge impacts of carbon policies. In this paper we consider, from an environmental policy-maker perspective, how carbon reduction policies impact the economic competitiveness of the manufacturing sector. Specifically, we focus on flowshop scheduling – which typically aims to minimize makespan for purely economic objectives – and consider how three common carbon reduction policies – namely, taxes on emissions, baselines on emissions, and emissions trading schemes – can create competitive green flowshops that balance minimization of makespan and carbon emissions. The goal is to enable policy-makers to understand how to set policies and control parameters to achieve environmental objectives while ensuring global economic competitiveness of industry. We initially present a set of mixed-integer linear programming (MILP) models for flowshop scheduling problems operating in a regulated environment in which each carbon reduction policy is adopted. We then introduce a bi-objective scheduling framework for the corresponding problem to obtain alternative solutions under each policy. These models and their computational results however, are not the main focus of the study, but are presented as a means to demonstrate how green policies co-exist with economic objectives, with policy-makers in control of the balance. To this end, based on financial data from Australia's carbon emissions profile, we provide a policy-oriented analysis of the models, and some managerial insights into the effect of scheduling strategies on carbon emissions under different reduction policies. These insights offer support to both environmental policy-makers and corporate production and sustainability managers to determine whether it is technically feasible and profitable to replace traditional scheduling strategies with environmentally friendly scheduling strategies. [ABSTRACT FROM AUTHOR]

Many women of reproductive age have poor diet quality and are at higher risk of chronic diseases such as diabetes. Triglycerides are a critical risk factor for chronic diseases, and although they can be influenced by diet, there are minimal dietary intervention studies identifying key foods/food groups that reduce triglycerides. We performed data simulation modelling to estimate the potential reductions in fasting triglycerides that could be achieved by different dietary strategies in reproductive age women. The model was created using data from the 2011-2013 Australian Health Survey and incorporated various factors such as demographics, nutrient intake, and plasma biomarkers. Multiple linear regression analysis was conducted to estimate triglyceride levels, considering nutrient intake and pre-determined covariates. Dietary scenarios were developed, reducing the consumption of processed/ultra-processed foods, while increasing the intake of minimally processed foods like fruits, vegetables, fish, and nuts. A total of 606 women were included. Reducing processed foods by 50% plus increasing intakes of fruits (75-225 g/day), vegetables (75-225 g/day), or nuts (10-40 g/day) decreased triglycerides by up to 4.3%. Additionally, incorporating 80 g/day of omega 3 fish (>800 mg long-chain omega 3/100 g) decreased triglycerides by 8.2%. The clinical relevance of lowering triglycerides for cardiometabolic disease management should be tested in dietary intervention studies in women.

Home health care (HHC) refers to the delivery of social, medical and paramedical services to people in their homes. Caregivers are assigned and routed to perform various tasks such as personal care and household chores at the client's homes. Minimising the total cost and satisfying the client requirements and preferences are critical in HHC. In this paper, we present a mixed-integer linear programming model for HHC routing and scheduling problems, which considers fair and balanced workload allocation of caregivers while minimising the total cost and addressing the client's needs. Due to the complexity of the problem, using a commercial solver is not practical for real size instances. Therefore, we develop a multi-steps clustering approach using Ordering Points and Agglomerative Hierarchical Clustering to solve the model. The proposed solution approach is applied on several test instances to examine its performance. We also apply the proposed model and solution approach on a case study in Australia. • Home health care planning problem with practical constraints is considered. • Clients and caregivers' satisfaction and balanced workload are considered. • A cluster-based framework is introduced to solve large-sized instances. • A standard benchmark for home care planning problem with preferences is generated. • Extensive numerical experiments based on real-life data are presented. [ABSTRACT FROM AUTHOR]

Purpose -- The value adding of each industry represents the value difference between the outputs and inputs of that industry. The purpose of this paper is to investigate the effect of international outsourcing on the value adding of industries. Design/methodology/approach -- Input output analysis and linear programming are used as for the research methodology. Australian Motor Vehicle and Parts Manufacturing (AMVPM) industry as an outsourcer and its main suppliers were selected for ten alternative international outsourcing scenarios in a case study. Findings -- In all international outsourcing scenarios except the baseline scenario, the reduction in the value adding of Australia would be approximately three times more than the value adding reduction of the AMVPM industry. Moreover, the international outsourcing ratio has negative relationships with the value adding of the Australian industries and positive relationship with the international industries. Finally, it was found that the degree of supplier's dependency on the orders of the outsourcer effects the percentage reduction of supplier's value adding. Research limitations/implications -- The aggregated data and the uncertainties in the technical coefficients are the main limitations of this research. The social and environmental costs, other tangible and intangible costs, as well as benefits of international outsourcing need to be further analysed in future research. Practical implications -- This study would help decision makers at the macro level to analyse and control the effect of international outsourcing on the value adding of their economies. Originality/value -- This study expands the current research at the industry level of international outsourcing by quantifying the effect of international outsourcing upon the value adding of all respected industries. [ABSTRACT FROM AUTHOR]

• We analyse climate variability/change effects on dryland wetland response to flows. • We use an emulator and an MC method to explore 4 K different flow conditions. • Wetland response for 30-year periods depends on average flow and flooding frequency. • Under current climate, wetland deterioration can occur 20% to 60% of the time. • Under a drier climate, deterioration can occur 85% to 95% of the time by 2100. During the Millennium Drought in southeast Australia (2001–2009), dryland wetlands experienced widespread ecological deterioration, which highlighted their vulnerability to natural climate variability and the potential effects of drying climate change. Here we use 30-year observed streamflow data (1991–2020) and numerical models to assess the impacts of climate variability and climate change on the Macquarie Marshes (the Marshes), a large floodplain wetland complex in the semi-arid region of New South Wales, Australia. A fast ecohydrologic emulator based on network linear programming with side constraints was developed to simulate the spatial and temporal responses of different wetland vegetation types to water regime. The emulator represents the wetland by a series of inter-connected level-pool reservoirs with the volume-discharge relationship obtained from a calibrated quasi-2d hydrodynamic model. The emulator reproduces daily flows and volume with good accuracy (Nash-Sutcliffe statistic ranging from 0.61 to 0.96) with 1/26,000 of the computational effort. We use the emulator to simulate the potential effects of climatic variability on vegetation by running the model over 30 years of observed data and 1000 statistically representative 30-year streamflow time series, which were generated using a stochastic model calibrated to the gauged flows. The collection of results for all 1000 contemporary simulations indicates the Marshes experience severe conditions 43% (± 18%) of the time in a 30-year period. We then ran an additional 6000 simulations to assess the combined impacts of climate variability and future climate change at the end of the century. For the driest future climates (-60% and -30% reduction in runoff), the Marshes remain in severe condition 89% (± 6%) and 63% (± 16%) of the time, respectively, while no major differences with respect to the contemporary conditions were found for the wetter future. Our results highlight the importance of quantifying the extent and uncertainty in the degradation of these ecosystems due to climate variability and change for informing management decisions. [Display omitted] [ABSTRACT FROM AUTHOR]

This article adopts a data envelopment analysis (DEA) bootstrap approach to measure the technical efficiency and scale properties of Australian restaurant operations. Four inputs and two outputs are used in the analysis, covering 105 restaurants. The results show that Australian restaurants incorporated in this study are operating at a low level of efficiency, with an average of around 46.17%. Inferences from the returns to scale are also in line with the efficiency results and indicate that most restaurants need to expand their production outputs in order to reach an optimum level of production. The article highlights and tests the important impact of factors such as restaurant size and management experience on the efficiency results. Other potential factors related to the external environment, as well as policy implications of the study, are also discussed. [ABSTRACT FROM PUBLISHER]

The aim of this article is to share the experience of using different software packages in the delivery of critical path networks in Engineering Management Science coded as ENG4004, in the Bachelor of Engineering and Bachelor of Engineering Technology programs offered by the University of Southern Queensland (USQ), a regional Australian University with excellence in developing e-learning (Good University Guides, 2001). The article describes how the authors use different software packages to solve the critical path network problems of the course. At times, more than one package will be required for the effective delivery of a topic or module of the course. The needs for the usage were also explained. The assessments of the course were also studied and reviewed. How the software packages met the objectives of the module was also discussed together with the desired learning outcomes of students. The preferred software was Production and Operations Management (POM-QM) for Windows 3. It was finally concluded that the actual costs to the university and students are not too much but students learning experience and satisfaction will be greatly improved. © 2009 Wiley Periodicals, Inc. Comput Appl Eng Educ 19: 26-39, 2011 [ABSTRACT FROM AUTHOR]

Abstract: It has been widely suggested that changing land use from annual to perennial crops reduces land and stream degradation due to salinisation. However, annual crops are financially attractive and increases in perennials can reduce stream flows with adverse effects on stream values. As such, salinity control is likely to involve tradeoffs between public and private costs and benefits. This study quantifies the expected on-farm economic and catchment-level water yield and salinity effects of altering land use among trees, perennial pastures and cereals. The structure of a two stage linear-programming (LP) process is described. The first stage is the MIDAS farm-level model of mixed cropping and sheep enterprises which provides inputs to a second stage catchment-level LP. It was concluded that perennial pastures can be used in conjunction with trees as a stream salinity-management tool in low to intermediate rainfall areas in New South Wales. The results indicate that land-use decisions should be informed by site-specific information if adverse effects on streams are to be avoided. [Copyright &y& Elsevier]

Pre-service teacher education is marked by linear and sequential programming which offers a plethora of strategies and methods (Cochran-Smith & Zeichner, 2005; Darling Hammond & Bransford, 2005; Grant & Zeichner, 1997). This paper emerges from a three year study within a core education subject in pre-service teacher education in Australia. This 'practitioner' research (Zeichner, 1999) engaged the problematics of authentic and meaningful learner-centred teaching and learning through an arts-based curriculum. Over the period of the study, two hundred and eighty pre-service teachers participated in a 'dialogical performance'(Conquergood, 2003) of pedagogy about curriculum and assessment through the construction of art about curriculum and assessment. The possibilities of an arts-based pedagogy in pre-service education were affirmed by the research. An enacted epistemological move by the teacher-educators led to similar shifts by the students. This opened a space for the reappearance of learner through engagements with identities, positionings and agency. This was an act of 'putting theory to work' (Lather, 2006, 2007) and invoked transgressive practices of academic discourses. [ABSTRACT FROM AUTHOR]

Transmission system structure has an essential effect on the reliability of the power system and electricity market performance, especially when producers bid strategically. As part of on-going research on the design of a robust algorithm for expansion planning of the transmission grid in the Australian electricity market, this paper presents a framework which addresses: (1) the security of power delivery to the load points of the transmission system in case of single line outages; (2) the minimization of transmission system lost load; (3) an efficient electricity market for market participants; (4) construction and maintenance costs of transmission augmentation options; and (5) operation efficiency of the transmission grid. The suggested algorithm benefits from the dynamic programming and sensitivity analysis approaches along with the aggregation method in its multi-criteria decision-making to locate the optimum configuration of a future transmission system. A set of indices, which account for impacts of the augmentation options of the transmission grid on five aforementioned reliability and market criteria, are proposed and used in the optimum framework for expansion planning of the transmission grid. Although the methodology is promising for expansion planning of the transmission system, considering the sensitivity analysis concept employed, the proposed methodology would be suitable to detect the sensitive areas of the transmission system to be expanded. The tool would be very useful in the case of large scale power systems for a smart reduction of the transmission expansion options. The proposed methodology has been applied to a 6-bus and a modified IEEE 30-bus test system to show the effectiveness of the sensitivity-based algorithm. [ABSTRACT FROM AUTHOR]

Although several forage species such as perennial ryegrass are predominant, there is a wide range of forage species that could be grown in subtropical and temperate regions in Australia as dairy pastures. These species have differing seasonal patterns of growth, nutrient quality, and water-use efficiency, as demonstrated in a large experiment evaluating over 30 species at the University of Sydney (Camden, New South Wales, Australia). Some species can be grazed, whereas others require mechanical harvesting, which incurs a further cost. Previous comparisons of species that relied on yield of dry matter per unit of some input (typically land or water) did not simultaneously take into account the season in which forage is produced, or other factors related to the costs of production and delivery to the cows. To effectively compare the profitability of individual species, or combinations of species, requires the use of a whole-farm, multiperiod model. Linear programming was used to find the most profitable mix of forage species for an irrigated dairy farm in a warm temperate irrigation region of New South Wales, Australia. It was concluded that for a typical farmer facing the prevailing milk and purchased feed prices with average milk production per cow, the most profitable mix of species would include a large proportion of perennial ryegrass (Lolium perenne) and prairie grass (Bromus willdenowii). The result was robust to changes in seasonal milk pricing and a move from year-round to a more seasonal calving pattern. [ABSTRACT FROM AUTHOR]

We used Data Envelopment Analysis to evaluate cost efficiency of Australian banks in producing banking services and profit between 1995 and 2002. Empirical results indicate the major banks have improved their efficiency in producing banking services and profit, while the regional banks have experienced little change in the efficiency of producing banking services, and a decline in the efficiency of producing profit. An attempt is made to relate the changes in efficiency to stock returns. Results indicate that for our sample, changes in firm efficiency are reflected in stock returns. [ABSTRACT FROM AUTHOR]

Forest biomass (FB) could supply more of Australia's energy needs, but delivered costs must be reduced for it to be a viable energy source. Operational planning is critical to reducing delivered costs as it determines actual activities, though few operational FB supply chain (FBSC) planning tools have been published. This paper presents a "proof-of-concept" operational FBSC decision support system (DSS) to schedule FB deliveries for eight weeks from roadside storage for the least cost, taking in account moisture content changes. Four mathematical models are compared, solving a linear formulation of the FB delivery problem in terms of solution speed and delivered cost, and the practicality of implementing the solutions. The best performing model was a Greedy algorithm as it produced solutions not significantly different from those of the tested linear programming solver and was readily modified to significantly improve solution implementation through the addition of a non-linear element. FBSC planning tools typically assume accurate knowledge of stored FB quantities and that little or no rainfall occurs during storage. In practice, stored FB quantity estimates can be inaccurate due to variation in the bulk density of the piles. Improving these estimates is a critical area for future research. This study found that simulated rainfall with <20 mm during the first week of the scheduled period did not significantly effect delivered costs. [ABSTRACT FROM AUTHOR]

The electrification of large-scale bus depots will bring challenges for bus depot operators (BDOs) aiming to minimize operational costs. A potential solution for BDOs managing electric buses (EBs) with large batteries that are capable of vehicle-to-grid (V2G) operational functionalities, along with on-site generation facilities, is to actively participate in the energy market. This paper proposed a novel two-stage multi-objective stochastic optimization-based energy management system (EMS) for BDOs to trade energy in a day-ahead (DA) energy market while considering the expected cost of energy imbalances in the real-time (RT) market. The optimization model for charge–discharge scheduling is based on a mixed-integer linear programming approach. The uncertainties associated with the DA forecast are complemented by a stochastic model. Minimizing the cost of electricity and the penalty costs for battery capacity degradation are the objectives that need to be met simultaneously. The proposed EMS is evaluated using simulation studies considering a hypothetical bus depot in Australia. The effectiveness of the proposed EMS for overall financial savings is validated by comparing its performance with state-of-the-art scheduling strategies. Results show that the net energy cost for the proposed EMS is 38% lower compared to a deterministic scheduling strategy that does not allow V2G flexibilities, 33% lower compared to a deterministic scheduling strategy that allows V2G flexibilities and 17% lower compared to a stochastic scheduling strategy that minimizes overall costs. [ABSTRACT FROM AUTHOR]

Forest biofuel delivered costs are generally uncompetitive with fossil fuels. Drying forest biofuel can potentially reduce delivered costs through weight reductions and net calorific value increases. The study examined the impact of roadside drying (RD) and use of high-volumetric capacity trucks on delivered costs of Pinus radiata pulp-logs and logging residue (LR) chips supplying a gasification plant. Five truck configurations: 6-axle semi-trailers; 9-axle B-doubles; proposed high-volumetric (HV) capacity versions of these trucks (HV semi-trailers and B-doubles); and 11-axle pocket road trains (PRT), were investigated across six supply areas using a forest biomass supply chain tool. Without RD all truck configurations were weight limited transporting logs, and all (except HV semi-trailers and B-doubles) were volume limited transporting LR chips. Post-RD all truck configurations were volume limited transporting logs or LR chips, (except HV B-doubles transporting logs). RD considerably reduced delivered costs: PRT (22%), B-doubles (24%), semi-trailers (25%) for logs and PRT (28%), B-doubles (29%), semi-trailers (30%) for LR chips. Delivered cost differences between truck configurations reflected transport cost differences. Without RD, truck trips transporting log were directly related to truck weight capacity. Additional volumetric capacity enabled HV semi-trailers and B-doubles to transport 6% and 4% more LR chips than standard versions, respectively, with equivalent truck trip reductions. RD weight reductions were: logs (33%); LR chips (53%), with consequent reductions in truck trips. PRTs required fewest truck trips to transport logs and LR chips without RD and the second fewest for logs post-RD due to their high weight and volumetric capacities. • Delivered log and residue costs were examined using a supply chain modelling tool. • Delivered cost reductions from roadside drying were considerable. • Cost reductions resulted from drying weight losses and net calorific value gains. • High-volume trucks combined with roadside drying produced the greatest gains. [ABSTRACT FROM AUTHOR]

• A framework for aggregating large-scale prosumers in electricity markets is proposed. • The proposed bi-level framework is linearized by duality theory and big-M method. • Cases studies based on 120,000 prosumers from Australia are conducted. • Increasing prosumers enlarges the gap between strategic and non-strategic bidding. Increased penetration of distributed energy resources is unleashing the flexibility of large-scale prosumers in deregulated markets. To explore prosumers' potential market revenues, some existing studies have focused on the strategic bidding of prosumers aggregation. A majority of those studies assume the price-taker role of the aggregator while a few studies assume the price-maker role of the aggregator. However, it remains an open question as to how the increasing number of prosumers influences the profit of a strategic aggregator. Therefore, we conduct a numerical analysis in this paper to quantify the profits of aggregating large-scale prosumers. A stochastic bi-level optimization model is proposed to depict the strategic behavior of prosumers aggregation bidding in joint energy and regulation markets. This bi-level model is transformed into a mixed-integer linear programming model by employing the Karush-Kuhn-Tucker conditions based on strong duality theory. Case studies based on 120,000 prosumers from Australia demonstrate that the strategic bidding behavior of an aggregator can lead to a 7.5% decrease in operation costs, and increasing the number of prosumers will lead to a larger gap between non-strategic and strategic behavior. [ABSTRACT FROM AUTHOR]

Although a handful of forage species such as perennial ryegrass are predominant, there are a wide range of forage species that can be grown in sub tropical and temperate regions in Australia as dairy pastures. These species have differing seasonal yields, nutrient quality and water use efficiency characteristics, as demonstrated in a large water use efficiency study of 30 species being undertaken at the University of Sydney in New South Wales, Australia. Some species can be grazed, while others require mechanical harvesting that incurs a further cost. Previous comparisons of species that relied on yields of dry matter per unit of some input (typically land or water) cannot simultaneously take into account the season in which forage is produced, or other factors related to the costs of production and delivery to the cows. To effectively compare the profitability of individual species, or combinations of species, requires the use of a whole-farm model. Linear programming was used to find the most profitable mix of forage species for an irrigated dairy farm. It was concluded that a mix of species was most profitable under the conditions faced by a typical dairy farmer situated in an irrigation region of New South Wales, Australia. [ABSTRACT FROM AUTHOR]