Scheduling techniques to optimise rail operations

In Australia, railway systems play a vital role in transporting the sugarcane crop from farms to mills. The sugarcane transport system is very complex and uses daily schedules, consisting of a set of locomotives runs, to satisfy the requirements of the mill and harvesters. The total cost of sugarcane transport operations is very high; over 35% of the total cost of sugarcane production in Australia is incurred in cane transport. Efficient schedules for sugarcane transport can reduce the cost and limit the negative effects that this system can have on the raw sugar production system. There are several benefits to formulating the train scheduling problem as a blocking parallel-machine job shop scheduling (BPMJSS) problem, namely to prevent two trains passing in one section at the same time; to keep the train activities (operations) in sequence during each run (trip) by applying precedence constraints; to pass the trains on one section in the correct order (priorities of passing trains) by applying disjunctive constraints; and, to ease passing trains by solving rail conflicts by applying blocking constraints and Parallel Machine Scheduling. Therefore, the sugarcane rail operations are formulated as BPMJSS problem. A mixed integer programming and constraint programming approaches are used to describe the BPMJSS problem. The model is solved by the integration of constraint programming, mixed integer programming and search techniques. The optimality performance is tested by Optimization Programming Language (OPL) and CPLEX software on small and large size instances based on specific criteria. A real life problem is used to verify and validate the approach. Constructive heuristics and new metaheuristics including simulated annealing and tabu search are proposed to solve this complex and NP-hard scheduling problem and produce a more efficient scheduling system. Innovative hybrid and hyper metaheuristic techniques are developed and coded using C# language to improve the solutions quality and CPU time. Hybrid techniques depend on integrating heuristic and metaheuristic techniques consecutively, while hyper techniques are the complete integration between different metaheuristic techniques, heuristic techniques, or both.

Agronomic and economic evaluation of irrigation strategies on cotton lint yield in Australia

Cotton is one of the most important irrigated crops in subtropical Australia. In recent years, cotton production has been severely affected by the worst drought in recorded history, with the 2007–08 growing season recording the lowest average cotton yield in 30 years. The use of a crop simulation model to simulate the long-term temporal distribution of cotton yields under different levels of irrigation and the marginal value for each unit of water applied is important in determining the economic feasibility of current irrigation practices. The objectives of this study were to: (i) evaluate the CROPGRO-Cotton simulation model for studying crop growth under deficit irrigation scenarios across ten locations in New South Wales (NSW) and Queensland (Qld); (ii) evaluate agronomic and economic responses to water inputs across the ten locations; and (iii) determine the economically optimal irrigation level. The CROPGRO-Cotton simulation model was evaluated using 2 years of experimental data collected at Kingsthorpe, Qld. The model was further evaluated using data from nine locations between northern NSW and southern Qld. Long-term simulations were based on the prevalent furrowirrigation practice of refilling the soil profile when the plant -available soil water content is<50%. The model closely estimated lint yield for all locations evaluated. Our results showed that the amounts of water needed to maximise profit and maximise yield are different, which has economic and environmental implications. Irrigation needed to maximise profits varied with both agronomic and economic factors, which can be quite variable with season and location. Therefore, better tools and information that consider the agronomic and economic implications of irrigation decisions need to be developed and made available to growers.

Factors affecting technical efficiency of rice farmers in village reservoir irrigation systems of Sri Lanka

Given the importance of water for rice production, this study examines the factors affecting the technical efficiency (TE) of irrigated rice farmers in village irrigation systems (VIS) in Sri Lanka. Primary data were collected from 460 rice farmers in the Kurunagala District, Sri Lanka, to estimate a stochastic translog production frontier for rice production. The mean TE of rice farming in village irrigation was found to be 0.72, although 63% of rice farmers exceeded this average. The most influential factors of TE are membership of Farmer Organisations (FOs) and the participatory rate in collective actions organised by FOs. The results suggest that enhancement of co-operative arrangements of farmers by strengthening the membership of FOs is considered important for increasing TE in rice farming in VIS.

Realistic irrigation visualization in a surgical wound debridement simulator

Wound debridement refers to the removal of necrotic, devitalized, or contaminated tissue and/or foreign material to promote wound healing. Surgical debridement uses sharp instruments to cut dead tissue from a wound and it is the quickest and most efficient method of debridement. A wound debridement simulator [1,2] can ensure that a medical trainee is competent prior to performing a procedure on a genuine patient. Irrigation is performed at different stages of debridement in order to remove debris and reduce the bacteria count through rinsing the wound. This paper presents a novel approach for realistic irrigation visualization based on texture representations of debris. This approach applies image processing techniques to a series of images, which model the cleanliness of the wound. The active texture is generated and updated dynamically based on the irrigation state, location, and range. Presented results demonstrate that texture mapping and image processing techniques can provide effective and efficient solutions for irrigation visualization in the wound debridement simulator.

Soil N2O and CO2 emissions from cotton in Australia under varying irrigation management

Irrigation is known to stimulate soil microbial carbon and nitrogen turnover and potentially the emissions of nitrous oxide (N2O) and carbon dioxide (CO2). We conducted a study to evaluate the effect of three different irrigation intensities on soil N2O and CO2 fluxes and to determine if irrigation management can be used to mitigate N2O emissions from irrigated cotton on black vertisols in South-Eastern Queensland, Australia. Fluxes were measured over the entire 2009/2010 cotton growing season with a fully automated chamber system that measured emissions on a sub-daily basis. Irrigation intensity had a significant effect on CO2 emission. More frequent irrigation stimulated soil respiration and seasonal CO2 fluxes ranged from 2.7 to 4.1 Mg-C ha−1 for the treatments with the lowest and highest irrigation frequency, respectively. N2O emission happened episodic with highest emissions when heavy rainfall or irrigation coincided with elevated soil mineral N levels and seasonal emissions ranged from 0.80 to 1.07 kg N2O-N ha−1 for the different treatments. Emission factors (EF = proportion of N fertilizer emitted as N2O) over the cotton cropping season, uncorrected for background emissions, ranged from 0.40 to 0.53 % of total N applied for the different treatments. There was no significant effect of the different irrigation treatments on soil N2O fluxes because highest emission happened in all treatments following heavy rainfall caused by a series of summer thunderstorms which overrode the effect of the irrigation treatment. However, higher irrigation intensity increased the cotton yield and therefore reduced the N2O intensity (N2O emission per lint yield) of this cropping system. Our data suggest that there is only limited scope to reduce absolute N2O emissions by different irrigation intensities in irrigated cotton systems with summer dominated rainfall. However, the significant impact of the irrigation treatments on the N2O intensity clearly shows that irrigation can easily be used to optimize the N2O intensity of such a system.

Nitrous oxide emissions from irrigated wheat in Australia : impact of irrigation management

Background and Aims: Irrigation management affects soil water dynamics as well as the soil microbial carbon and nitrogen turnover and potentially the biosphere-atmosphere exchange of greenhouse gasses (GHG). We present a study on the effect of three irrigation treatments on the emissions of nitrous oxide (N2O) from irrigated wheat on black vertisols in South-Eastern Queensland, Australia. Methods: Soil N2O fluxes from wheat were monitored over one season with a fully automated system that measured emissions on a sub-daily basis. Measurements were taken from 3 subplots for each treatment within a randomized split-plot design. Results: Highest N2O emissions occurred after rainfall or irrigation and the amount of irrigation water applied was found to influence the magnitude of these “emission pulses”. Daily N2O emissions varied from -0.74 to 20.46 g N2O-N ha-1 day-1 resulting in seasonal losses ranging from 0.43 to 0.75 kg N2O N ha-1 season -1 for the different irrigation treatments. Emission factors (EF = proportion of N fertilizer emitted as N2O) over the wheat cropping season, uncorrected for background emissions, ranged from 0.2 to 0.4% of total N applied for the different treatments. Highest seasonal N2O emissions were observed in the treatment with the highest irrigation intensity; however, the N2O intensity (N2O emission per crop yield) was highest in the treatment with the lowest irrigation intensity. Conclusions: Our data suggest that timing and amount of irrigation can effectively be used to reduce N2O losses from irrigated agricultural systems; however, in order to develop sustainable mitigation strategies the N2O intensity of a cropping system is an important concept that needs to be taken into account.

Scheduling decisions and their dynamic consequences on construction performance

Construction practitioners often experience unexpected results of their scheduling-related decisions. This is mainly due to lack of understanding of the dynamic nature of construction system. However, very little attention has been given to its significant importance and few empirical studies have been undertaken on this issue. This paper, therefore, analyzes the effect of aggressive scheduling, overtime, resource adding, and schedule slippage on construction performance, focusing on workers’ reactions to those scheduling decisions. Survey data from 102 construction practitioners in 38 construction sites are used for the analysis. The results indicate that efforts to increase work rate by working overtime, resource adding, and aggressive scheduling can be offset due to losses in productivity and quality. Based on the research findings, practical guidelines are then discussed to help site managers to effectively deal with the dynamics of scheduling and improve construction performance.

Phosphorus as a limiting factor on sustainable greywater irrigation

Water reuse through greywater irrigation has been adopted worldwide and has been proposed as a potential sustainable solution to increased water demands. Despite widespread adoption there is limited domestic knowledge of greywater reuse, there is no pressure to produce lowlevel phosphorus products and current guidelines and legislation, such as those in Australia, may be inadequate due to the lack of long-term data to provide a sound scientific basis. Research has clearly identified phosphorus as a potential environmental risk to waterways from many forms of irrigation. To assess the sustainability of greywater irrigation, this study compared four residential lots that had been irrigated with greywater for four years and adjacent non-irrigated lots that acted as controls. Each lot was monitored for the volume of greywater applied and selected physic-chemical water quality parameters and soil chemistry profiles were analysed. The non-irrigated soil profiles showed low levels of phosphorus and were used as controls. The Mechlich3 Phosphorus ratio (M3PSR) and Phosphate Environmental Risk Index (PERI) were used to determine the environmental risk of phosphorus leaching from the irrigated soils. Soil phosphorus concentrations were compared to theoretical greywater irrigation loadings. The measured phosphorus soil concentrations and the estimated greywater loadings were of similar magnitude. Sustainable greywater reuse is possible; however incorrect use and/or a lack of understanding of how household products affect greywater can result in phosphorus posing a significant risk to the environment.

A hybrid constructive heuristic and simulated annealing for railway crew scheduling

Railway crew scheduling problem is the process of allocating train services to the crew duties based on the published train timetable while satisfying operational and contractual requirements. The problem is restricted by many constraints and it belongs to the class of NP-hard. In this paper, we develop a mathematical model for railway crew scheduling with the aim of minimising the number of crew duties by reducing idle transition times. Duties are generated by arranging scheduled trips over a set of duties and sequentially ordering the set of trips within each of duties. The optimisation model includes the time period of relief opportunities within which a train crew can be relieved at any relief point. Existing models and algorithms usually only consider relieving a crew at the beginning of the interval of relief opportunities which may be impractical. This model involves a large number of decision variables and constraints, and therefore a hybrid constructive heuristic with the simulated annealing search algorithm is applied to yield an optimal or near-optimal schedule. The performance of the proposed algorithms is evaluated by applying computational experiments on randomly generated test instances. The results show that the proposed approaches obtain near-optimal solutions in a reasonable computational time for large-sized problems.

An interactive planning and scheduling framework for optimising pits-to-crushers operations

In this paper, an interactive planning and scheduling framework are proposed for optimising operations from pits to crushers in ore mining industry. Series of theoretical and practical operations research techniques are investigated to improve the overall efficiency of mining systems due to the facts that mining managers need to tackle optimisation problems within different horizons and with different levels of detail. Under this framework, mine design planning,mine production sequencing and mine transportation scheduling models are integrated and interacted within a whole optimisation system. The proposed integrated framework could be used by mining industry for reducing equipment costs, improving the production efficiency and maximising the net present value.

A short-term production scheduling methodology for open-pit mines

A multi-resource multi-stage scheduling methodology is developed to solve short-term open-pit mine production scheduling problems as a generic multi-resource multi-stage scheduling problem. It is modelled using essential characteristics of short-term mining production operations such as drilling, sampling, blasting and excavating under the capacity constraints of mining equipment at each processing stage. Based on an extended disjunctive graph model, a shifting-bottleneck-procedure algorithm is enhanced and applied to obtain feasible short-term open-pit mine production schedules and near-optimal solutions. The proposed methodology and its solution quality are verified and validated using a real mining case study.

A flexible optimisation model for the railway crew scheduling problem

Addressing the Crew Scheduling Problem (CSP) in transportation systems can be too complex to capture all details. The designed models usually ignore or simplify features which are difficult to formulate. This paper proposes an alternative formulation using a Mixed Integer Programming (MIP) approach to the problem. The optimisation model integrates the two phases of pairing generation and pairing optimisation by simultaneously sequencing trips into feasible duties and minimising total elapsed time of any duty. Crew scheduling constraints in which the crew have to return to their home depot at the end of the shift are included in the model. The flexibility of this model comes in the inclusion of the time interval of relief opportunities, allowing the crew to be relieved during a finite time interval. This will enhance the robustness of the schedule and provide a better representation of real-world conditions.

Nitrous oxide emissions from fertilized, irrigated cotton (Gossypium hirsutum L.) in the Aral Sea Basin, Uzbekistan : influence of nitrogen applications and irrigation practices

Nitrous oxide emissions were monitored at three sites over a 2-year period in irrigated cotton fields in Khorezm, Uzbekistan, a region located in the arid deserts of the Aral Sea Basin. The fields were managed using different fertilizer management strategies and irrigation water regimes. N2O emissions varied widely between years, within 1 year throughout the vegetation season, and between the sites. The amount of irrigation water applied, the amount and type of N fertilizer used, and topsoil temperature had the greatest effect on these emissions. Very high N2O emissions of up to 3000 μg N2O-N m−2 h−1 were measured in periods following N-fertilizer application in combination with irrigation events. These “emission pulses” accounted for 80–95% of the total N2O emissions between April and September and varied from 0.9 to 6.5 kg N2O-N ha−1.. Emission factors (EF), uncorrected for background emission, ranged from 0.4% to 2.6% of total N applied, corresponding to an average EF of 1.48% of applied N fertilizer lost as N2O-N. This is in line with the default global average value of 1.25% of applied N used in calculations of N2O emissions by the Intergovernmental Panel on Climate Change. During the emission pulses, which were triggered by high soil moisture and high availability of mineral N, a clear diurnal pattern of N2O emissions was observed, driven by daily changes in topsoil temperature. For these periods, air sampling from 8:00 to 10:00 and from 18:00 to 20:00 was found to best represent the mean daily N2O flux rates. The wet topsoil conditions caused by irrigation favored the production of N2O from NO3− fertilizers, but not from NH4+ fertilizers, thus indicating that denitrification was the main process causing N2O emissions. It is therefore argued that there is scope for reducing N2O emission from irrigated cotton production; i.e. through the exclusive use of NH4+ fertilizers. Advanced application and irrigation techniques such as subsurface fertilizer application, drip irrigation and fertigation may also minimize N2O emission from this regionally dominant agro-ecosystem.