An Integrated Territory Planning and Vehicle Routing Approach for a Multi-Objective Residential Waste Collection Problem

In this paper, we address a multi-objective residential waste collection problem with an integrated territory planning and vehicle routing approach. Dividing the problem into territories enables drivers to carry out the same route every week so they get familiar with it and residents put out their bins at the appropriate time. Another benefit is to reduce the computation time for large problems, since the complex characteristics of the involved vehicle routing problem make it otherwise difficult to solve. There are three characteristics that are important for good territory planning: minimum overlap, minimum travel time, and balanced workload. The purpose of this paper is to investigate the influence these three objectives have on each other, since they might be contradictory. Moreover, an Adaptive Large Neighborhood Search (ALNS) algorithm is developed for this specific problem which uses a K-means algorithm to generate the initial solution for territories. The results with the three objectives are shown to be useful for planners seeking to make informed decisions through the trade-off across different solutions with the Pareto frontiers provided. Moreover, the ALNS algorithm is shown to find good quality solutions in a reasonable computational time.

Aspects of airline crew rostering

Airline crew rostering is a complicated planning-type problem, and its objective is to assemble pairings into schedules that maximise the satisfaction levels of crews. The rostering process focuses on achieving a more balanced workload distribution among the crewmembers that allows designing rosters in the interest of the crew. The main purpose of the paper was to explain the fundamental aspects of airline crew rostering and its impact on crewmembers’ fatigue. Additionally, the research identified mitigation measures that airlines should make to combat or mitigate crewmembers’ fatigue when designing their rosters. The paper also allowed readers to understand the effects of fatigue on crew’s alertness and performance. The qualitative research methods (such as literature review) was used to understand the complexity of the airline crew rostering, the flight and duty time limitations, crew’s rest requirement and crewmembers’ fatigue. The survey was used as the quantitative research method to identify crewmembers’ satisfaction with their rosters that would help to optimise the rostering process. An online survey (using Google Forms) was distributed to potential respondents (experienced crewmembers) via email addresses and online platforms. Respondents were asked 18 close ended questions divided into two parts (demographic and operational experience). One hundred eleven responses were gathered, which showed that age plays a crucial role in crewmembers’ fatigue. In addition, cargo pilots are usually more dissatisfied with their rosters due to exhausting flight duty periods at nights.

PCONV: The Missing but Desirable Sparsity in DNN Weight Pruning for Real-Time Execution on Mobile Devices

Model compression techniques on Deep Neural Network (DNN) have been widely acknowledged as an effective way to achieve acceleration on a variety of platforms, and DNN weight pruning is a straightforward and effective method. There are currently two mainstreams of pruning methods representing two extremes of pruning regularity: non-structured, fine-grained pruning can achieve high sparsity and accuracy, but is not hardware friendly; structured, coarse-grained pruning exploits hardware-efficient structures in pruning, but suffers from accuracy drop when the pruning rate is high. In this paper, we introduce PCONV, comprising a new sparsity dimension, – fine-grained pruning patterns inside the coarse-grained structures. PCONV comprises two types of sparsities, Sparse Convolution Patterns (SCP) which is generated from intra-convolution kernel pruning and connectivity sparsity generated from inter-convolution kernel pruning. Essentially, SCP enhances accuracy due to its special vision properties, and connectivity sparsity increases pruning rate while maintaining balanced workload on filter computation. To deploy PCONV, we develop a novel compiler-assisted DNN inference framework and execute PCONV models in real-time without accuracy compromise, which cannot be achieved in prior work. Our experimental results show that, PCONV outperforms three state-of-art end-to-end DNN frameworks, TensorFlow-Lite, TVM, and Alibaba Mobile Neural Network with speedup up to 39.2 ×, 11.4 ×, and 6.3 ×, respectively, with no accuracy loss. Mobile devices can achieve real-time inference on large-scale DNNs.

THE BALANCED PRODUCTION LOAD OF A MACHINE-ENGINEERING ORGANIZATION

The article deals with an approach to calculation of equipment, employee or work centers load during the production plan forming by machine engineering organizations. The calculations are based on the duration of manufacturing operations and the electronic structure of items, and provide the most balanced workload at the shortest time of production. The article describes the model of item production and the technique of production plan forming according to each work center with the set of calculation constraints. It also calculates the efficiency of an equipment load and time of production based on the current production plan. The calculation of load plan for work centers is provided by auxiliary software module of an interactive web-resource using the T-SQL.

Collaboration Two-Way

Collaborative writing has been found to lead to more productive writing processes and enhanced final products in terms of a richer vocabulary, more accurate grammar, and better organization. The present study expands on this research strand by exploring if different group writing processes affect the quality of wiki texts composed by groups of intermediate German L2 learners. Defining true collaborative writing as involving both a balanced workload and a joint responsibility for the product from all group members, it measured collaboration in two ways. Results indicate that most of the 19 groups in this study had a somewhat unbalanced workload with wide variability in editing group members’ contributions. Although the wiki texts differed greatly with regard to quantitative measures of length, accuracy and cohesion, no correlation was found in terms of workload or co-ownership. While holistic ratings of the texts concerning accuracy and cohesion seemed at times incongruent with the analytic measures, the raters’ comments provided a perspective that captured facets and nuances of a text that the analytic indicators did not.

Computing voxelised representations of macromolecular surfaces

Voxel-based representations of surfaces have received a lot of interest in bioinformatics and computational biology as a simple and effective way of representing geometrical and physicochemical properties of proteins and other biomolecules. Processing such surfaces for large molecules can be challenging, as space-demanding data structures with associated high computational costs are required. In this paper, we present a methodology for the fast computation of voxelised macromolecular surface representations (namely the van der Waals, solvent-accessible and solvent-excluded surfaces). The proposed method implements a spatial slicing procedure on top of compact data structures to efficiently calculate the three molecular surface representations at high-resolutions, in parallel. The spatial slicing protocol ensures a balanced workload distribution and allows the computation of the solvent-excluded surface with minimal synchronisation and communication between processes. This is achieved by adapting a multi-step region-growing EDT algorithm. At each step, distance values are first calculated independently for every slice, then, a small portion of the borders’ information is exchanged between adjacent slices. Very little process communication is also required in the pocket detection procedure, where the algorithm distinguishes surface portions belonging to solvent-accessible pockets from cavities buried inside the molecule. Experimental results are presented to validate the proposed approach.