An ecology of centre-based child care

The studies in the thesis were derived from a program of research focused on centre-based child care in Australia. The studies constituted an ecological analysis as they examined proximal and distal factors which have the potential to affect children's developmental opportunities (Bronfenbrenner, 1979). The project was conducted in thirty-two child care centres located in south-east Queensland. Participants in the research included staff members at the centres, families using the centres and their children. The first study described the personal and professional characteristics of one hundred and forty-four child care workers, as well as their job satisfaction and job commitment. Factors impinging on the stability of care afforded to children were examined, specifically child care workers' intentions to leave their current position and actual staff turnover at a twelve month follow-up. This is an ecosystem analysis (Bronfenbrenner & Crouter, 1983), as it examined the world of work for carers; a setting not directly involving the developing child, but which has implications for children's experiences. Staff job satisfaction was focused on working with children and other adults, including parents and colleagues. Involvement with children was reported as being the most rewarding aspect of the work. This intrinsic satisfaction was enough to sustain caregivers' efforts to maintain their employment in child care programs. It was found that, while improving working conditions may help to reduce turnover, it is likely that moderate turnover rates will remain as child care staff work in relatively small centres and they leave in order to improve career prospects. Departure from a child care job appeared to be as much about improving career opportunities or changing personal circumstances, as it was about poor wages and working conditions. In the second study, factors that influence maternal satisfaction with child care arrangements were examined. The focus included examination of the nature and qualities of parental interaction with staff. This was a mesosystem analysis (Bronfenbrenner & Crouter, 1983), as it considered the links between family and child care settings. Two hundred and twenty-two questionnaires were returned from mothers whose children were enrolled in the participating centres. It was found that maternal satisfaction with child care encompassed the domains of child-centred and parent-centred satisfaction. The nature and range of responses in the quantitative and qualitative data indicated that these parents were genuinely satisfied with their children's care. In the prediction of maternal satisfaction with child care, single parents, mothers with high role satisfaction, and mothers who were satisfied with the frequency of staff contact and degree of supportive communication had higher levels of satisfaction with their child care arrangements. The third study described the structural and process variations within child care programs and examined program differences for compliance with regulations and differences by profit status of the centre, as a microsystem analysis (Bronfenbrenner, 1979). Observations were made in eighty-three programs which served children from two to five years. The results of the study affirmed beliefs that nonprofit centres are superior in the quality of care provided, although this was not to a level which meant that the care in for-profit centres was inadequate. Regulation of structural features of child care programs, per se, did not guarantee higher quality child care as measured by global or process indicators. The final study represented an integration of a range of influences in child care and family settings which may impact on development. Features of child care programs which predict children's social and cognitive development, while taking into account child and family characteristics, were identified. Results were consistent with other research findings which show that child and family characteristics and child care quality predict children's development. Child care quality was more important to the prediction of social development, while family factors appeared to be more predictive of cognitive/language development. An influential variable predictive of development was the period of time which the child had been in the centre. This highlighted the importance of the stability of child care arrangements. Child care quality features which had most influence were global ratings of the qualities of the program environment. However, results need to be interpreted cautiously as the explained variance in the predictive models developed was low. The results of these studies are discussed in terms of the implications for practice and future research. Considerations for an expanded view of ecological approaches to child care research are outlined. Issues discussed include the need to generate child care research which is relevant to social policy development, the implications of market driven policies for child care services, professionalism and professionalisation of child care work, and the need to reconceptualise child care research when the goal is to develop greater theoretical understanding about child care environments and developmental processes.

Modelling and solving train scheduling problems under capacity constraints

Many large coal mining operations in Australia rely heavily on the rail network to transport coal from mines to coal terminals at ports for shipment. Over the last few years, due to the fast growing demand, the coal rail network is becoming one of the worst industrial bottlenecks in Australia. As a result, this provides great incentives for pursuing better optimisation and control strategies for the operation of the whole rail transportation system under network and terminal capacity constraints. This PhD research aims to achieve a significant efficiency improvement in a coal rail network on the basis of the development of standard modelling approaches and generic solution techniques. Generally, the train scheduling problem can be modelled as a Blocking Parallel- Machine Job-Shop Scheduling (BPMJSS) problem. In a BPMJSS model for train scheduling, trains and sections respectively are synonymous with jobs and machines and an operation is regarded as the movement/traversal of a train across a section. To begin, an improved shifting bottleneck procedure algorithm combined with metaheuristics has been developed to efficiently solve the Parallel-Machine Job- Shop Scheduling (PMJSS) problems without the blocking conditions. Due to the lack of buffer space, the real-life train scheduling should consider blocking or hold-while-wait constraints, which means that a track section cannot release and must hold a train until the next section on the routing becomes available. As a consequence, the problem has been considered as BPMJSS with the blocking conditions. To develop efficient solution techniques for BPMJSS, extensive studies on the nonclassical scheduling problems regarding the various buffer conditions (i.e. blocking, no-wait, limited-buffer, unlimited-buffer and combined-buffer) have been done. In this procedure, an alternative graph as an extension of the classical disjunctive graph is developed and specially designed for the non-classical scheduling problems such as the blocking flow-shop scheduling (BFSS), no-wait flow-shop scheduling (NWFSS), and blocking job-shop scheduling (BJSS) problems. By exploring the blocking characteristics based on the alternative graph, a new algorithm called the topological-sequence algorithm is developed for solving the non-classical scheduling problems. To indicate the preeminence of the proposed algorithm, we compare it with two known algorithms (i.e. Recursive Procedure and Directed Graph) in the literature. Moreover, we define a new type of non-classical scheduling problem, called combined-buffer flow-shop scheduling (CBFSS), which covers four extreme cases: the classical FSS (FSS) with infinite buffer, the blocking FSS (BFSS) with no buffer, the no-wait FSS (NWFSS) and the limited-buffer FSS (LBFSS). After exploring the structural properties of CBFSS, we propose an innovative constructive algorithm named the LK algorithm to construct the feasible CBFSS schedule. Detailed numerical illustrations for the various cases are presented and analysed. By adjusting only the attributes in the data input, the proposed LK algorithm is generic and enables the construction of the feasible schedules for many types of non-classical scheduling problems with different buffer constraints. Inspired by the shifting bottleneck procedure algorithm for PMJSS and characteristic analysis based on the alternative graph for non-classical scheduling problems, a new constructive algorithm called the Feasibility Satisfaction Procedure (FSP) is proposed to obtain the feasible BPMJSS solution. A real-world train scheduling case is used for illustrating and comparing the PMJSS and BPMJSS models. Some real-life applications including considering the train length, upgrading the track sections, accelerating a tardy train and changing the bottleneck sections are discussed. Furthermore, the BPMJSS model is generalised to be a No-Wait Blocking Parallel- Machine Job-Shop Scheduling (NWBPMJSS) problem for scheduling the trains with priorities, in which prioritised trains such as express passenger trains are considered simultaneously with non-prioritised trains such as freight trains. In this case, no-wait conditions, which are more restrictive constraints than blocking constraints, arise when considering the prioritised trains that should traverse continuously without any interruption or any unplanned pauses because of the high cost of waiting during travel. In comparison, non-prioritised trains are allowed to enter the next section immediately if possible or to remain in a section until the next section on the routing becomes available. Based on the FSP algorithm, a more generic algorithm called the SE algorithm is developed to solve a class of train scheduling problems in terms of different conditions in train scheduling environments. To construct the feasible train schedule, the proposed SE algorithm consists of many individual modules including the feasibility-satisfaction procedure, time-determination procedure, tune-up procedure and conflict-resolve procedure algorithms. To find a good train schedule, a two-stage hybrid heuristic algorithm called the SE-BIH algorithm is developed by combining the constructive heuristic (i.e. the SE algorithm) and the local-search heuristic (i.e. the Best-Insertion- Heuristic algorithm). To optimise the train schedule, a three-stage algorithm called the SE-BIH-TS algorithm is developed by combining the tabu search (TS) metaheuristic with the SE-BIH algorithm. Finally, a case study is performed for a complex real-world coal rail network under network and terminal capacity constraints. The computational results validate that the proposed methodology would be very promising because it can be applied as a fundamental tool for modelling and solving many real-world scheduling problems.