Metaheuristic approaches to the hybrid flow shop scheduling problem with a cost-related criterion

In the paper, the flow-shop scheduling problem with parallel machines at each stage (machine center) is studied. For each job its release and due date as well as a processing time for its each operation are given. The scheduling criterion consists of three parts: the total weighted earliness, the total weighted tardiness and the total weighted waiting time. The criterion takes into account the costs of storing semi-manufactured products in the course of production and ready-made products as well as penalties for not meeting the deadlines stated in the conditions of the contract with customer. To solve the problem, three constructive algorithms and three metaheuristics (based one Tabu Search and Simulated Annealing techniques) are developed and experimentally analyzed. All the proposed algorithms operate on the notion of so-called operation processing order, i.e. the order of operations on each machine. We show that the problem of schedule construction on the base of a given operation processing order can be reduced to the linear programming task. We also propose some approximation algorithm for schedule construction and show the conditions of its optimality.

Critique groups : a technique for the author’s toolbox?

With a lack of places to gain an education in the craft of romance writing, novelists have few places to turn to gain real feedback. This paper investigates an alternative to textbooks, conferences, and workshops through an examination of the role provided to the writer by critique groups. How these groups work, how they benefit an author, and the critique groups as a whole are discussed. This work studies the form of Peer Assessment and Learning (PAL) and compares the technique used by educational institutions all over the world with the practice of author groups critiquing their own work. The research shows how a critique group can assist a writer to learn, grow and develop, helping to enhance the writer’s skills through constructive feedback, which gives them confidence to sell their work.

Academic career development workshop for research students and early career academics

For research students and early career academics, universities offer resources that help develop their research skills – for example, critical theory development, literature reviews, research methods, data analysis, writing skills, etc. However, building a successful career in academia poses a wide range of new challenges in addition to the pure academic craft of research. The resources and resilience one needs in order to shape an academic career path often appear ambiguous, particularly in the innately transformative field of Internet research. In response to feedback from AoIR members, this full-day workshop seeks to address this concern by offering a supportive and constructive environment to discuss career development related issues that are of specific interest to research students and early career academics.

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.

Thinking Collaboratively about the Peer-Review Process for Journal- Article Publication

In this conversation, Kevin K. Kumashiro shares his reflections on challenges to publishing anti-oppressive research in educational journals. He then invites eight current and former editors of leading educational research journals--William F. Pinar, Elizabeth Graue, Carl A. Grant, Maenette K. P. Benham, Ronald H. Heck, James Joseph Scheurich, Allan Luke, and Carmen Luke--to critique and expand on his analysis. Kumashiro begins the conversation by describing his own experiences submitting manuscripts to educational research journals and receiving comments by anonymous reviewers and journal editors. He suggests three ways to rethink the collaborative potential of the peer-review process: as constructive, as multilensed, and as situated. The eight current and former editors of leading educational research journals then critique and expand Kumashiro's analysis. Kumashiro concludes the conversation with additional reflections on barriers and contradictions involved in advancing anti-oppressive educational research in educational journals. (Contains 3 notes.)

Governors highway safety associations and transportation planning: Exploratory factor analysis and structural equation modeling

The Intermodal Surface Transportation Efficiency Act (ISTEA) of 1991 mandated the consideration of safety in the regional transportation planning process. As part of National Cooperative Highway Research Program Project 8-44, "Incorporating Safety into the Transportation Planning Process," we conducted a telephone survey to assess safety-related activities and expertise at Governors Highway Safety Associations (GHSAs), and GHSA relationships with metropolitan planning organizations (MPOs) and state departments of transportation (DOTs). The survey results were combined with statewide crash data to enable exploratory modeling of the relationship between GHSA policies and programs and statewide safety. The modeling objective was to illuminate current hurdles to ISTEA implementation, so that appropriate institutional, analytical, and personnel improvements can be made. The study revealed that coordination of transportation safety across DOTs, MPOs, GHSAs, and departments of public safety is generally beneficial to the implementation of safety. In addition, better coordination is characterized by more positive and constructive attitudes toward incorporating safety into planning.

Towards making a difference through a university-TAFE partnership : mentoring potential teacher aides

Universities promote partnerships as an investment of social capital that may benefit communities. Mentoring of university students in schools has become key to induction of education workplace practices. One such arrangement is the mentoring of students from TAFE who endeavour to become teacher aides. However, there is no theoretical model for mentoring teacher aides and, similar to mentoring preservice teachers, such practices vary in quality and quantity. What are mentors’ perceptions of mentoring potential teacher aides within school settings? This mixed-method research involves a survey with extended responses. The aim is to determine practices and strategies for mentoring potential teacher aides (PTAs). Results indicated that PTAs require induction about the school culture and infrastructure, which includes ethics, values, operational plans, awareness of facilities and a range of other inductions that would aid the PTA’s work practices. Findings also revealed that many of the mentoring practices employed for preservice teachers may be used for mentoring PTAs in school settings. Indeed, mentors require personal attributes to facilitate the mentoring process. They also indicated outlining the education system requirements as fundamental to workplace operations. In addition, as most PTAs work with students in the classroom, the mentor’s pedagogical knowledge can further assist PTAs to develop an understanding of effective pedagogical practices, particularly for small groups or one-on-one sessions. Finally, a mentor’s modelling of practices and providing constructive feedback about the PTA’s practices can assist the development of workplace operations. In conclusion, the survey employed in this study may assist organisations to develop protocols of practice for workplace mentors. PTAs require mentors who are versed in effective mentoring practices that can more readily guide them towards success.

Curriculum alignment: Exploring student perception of learning achievement measures

The importance of constructively aligned curriculum is well understood in higher education. Based on the principles of constructive alignment, this research considers whether student perception of learning achievement measures can be used to gain insights into how course activities and pedagogy are assisting or hindering students in accomplishing course learning goals. Students in a Marketing Principles course were asked to complete a voluntary survey rating their own progress on the intended learning goals for the course. Student perceptions of learning achievement were correlated with actual student learning, as measured by grade, suggesting that student perceptions of learning achievement measures are suitable for higher educators. Student perception of learning achievement measures provide an alternate means to understand whether students are learning what was intended, which is particularly useful for educators faced with large classes and associated restrictions on assessment. Further, these measures enable educators to simultaneously gather evidence to document the impact of teaching innovations on student learning. Further implications for faculty and future research are offered.

A pattern mining approach for information filtering systems

It is a big challenge to clearly identify the boundary between positive and negative streams for information filtering systems. Several attempts have used negative feedback to solve this challenge; however, there are two issues for using negative relevance feedback to improve the effectiveness of information filtering. The first one is how to select constructive negative samples in order to reduce the space of negative documents. The second issue is how to decide noisy extracted features that should be updated based on the selected negative samples. This paper proposes a pattern mining based approach to select some offenders from the negative documents, where an offender can be used to reduce the side effects of noisy features. It also classifies extracted features (i.e., terms) into three categories: positive specific terms, general terms, and negative specific terms. In this way, multiple revising strategies can be used to update extracted features. An iterative learning algorithm is also proposed to implement this approach on the RCV1 data collection, and substantial experiments show that the proposed approach achieves encouraging performance and the performance is also consistent for adaptive filtering as well.

A design science research roadmap

This paper proposes and synthesizes from previous design science(DS) methodological literature a structured and detailed DS Roadmap for the conduct of DS research. The Roadmap is a general guide for researchers to carry out DS research by suggesting reasonably detailed activities.Though highly tentative, it is believed the Roadmap usefully inter-relates many otherwise seemingly disparate, overlapping or conflicting concepts. It is hoped the DS Roadmap will aid in the planning, execution and communication of DS research,while also attracting constructive criticism, improvements and extensions. A key distinction of the Roadmap from other DS research methods is its breadth of coverage of DS research aspects and activities; its detail and scope. We demonstrate and evaluate the Roadmap by presenting two case studies in terms of the DS Roadmap.

Neural network learning:theoretical foundations

This important work describes recent theoretical advances in the study of artificial neural networks. It explores probabilistic models of supervised learning problems, and addresses the key statistical and computational questions. Chapters survey research on pattern classification with binary-output networks, including a discussion of the relevance of the Vapnik Chervonenkis dimension, and of estimates of the dimension for several neural network models. In addition, Anthony and Bartlett develop a model of classification by real-output networks, and demonstrate the usefulness of classification with a "large margin." The authors explain the role of scale-sensitive versions of the Vapnik Chervonenkis dimension in large margin classification, and in real prediction. Key chapters also discuss the computational complexity of neural network learning, describing a variety of hardness results, and outlining two efficient, constructive learning algorithms. The book is self-contained and accessible to researchers and graduate students in computer science, engineering, and mathematics