Metaheuristics for the Order Batching Problem in Manual Order Picking Systems

In manual order picking systems, order pickers walk or drive through a distribution warehouse in order to collect items which are requested by (internal or external) customers. In order to perform these operations effciently, it is usually required that customer orders are combined into (more substantial) picking orders of limited size. The Order Batching Problem considered in this paper deals with the question of how a given set of customer orders should be combined such that the total length of all tours is minimized which are necessary to collect all items. The authors introduce two metaheuristic approaches for the solution of this problem; the rst one is based on Iterated Local Search, the second one on Ant Colony Optimization. In a series of extensive numerical experiments, the newly developed approaches are benchmarked against classic solution methods. It is demonstrated that the proposed methods are not only superior to existing methods, but provide solutions which may allow for operating distribution warehouses signicantly more effcient.Warehouse Management, Order Picking, Order Batching, Iterated Local Search, Ant Colony Optimization

Are the Chinese in Africa More Innovative than the Africans? Comparing Chinese and Nigerian Entrepreneurial Migrants’ Cultures of Innovation

The remarkable influx of Chinese migrant entrepreneurs in West Africa has been met with growing resistance from established African entrepreneurs. Whether the former have a competitive edge over the latter because of distinctive sociocultural traits or whether the Chinese's supposed effectiveness is just a characteristic feature of any trading diaspora is open to question. This comparative exploratory study of Chinese and Nigerian entrepreneurial migrants in Ghana and Benin provides initial answers to these questions. Apparently, the cultural stimuli for migrant drivers of change are not restricted to inherited value systems or religions, such as a Protestant ethic or Confucianism; rather, they are continually adapted and invented anew by transnational migration networks in a globalized world. There is no evidence of the supposed superiority of the innovative culture of Chinese entrepreneurial migrants versus that of African entrepreneurial migrants. Rather, there exist trading diasporas which have a generally enhanced innovative capacity vis-àvis local entrepreneurs, regardless of the national culture in which they are embedded. In addition, the rivalry of Chinese and Nigerian migrant entrepreneurs in African markets does not necessarily lead to the often suspected cut-throat competition. Often the actions of each group are complementary to those of the other. Under certain conditions they even contribute to poverty alleviation in the host country.trading diasporas, international migration, entrepreneurs, culture, innovation, SMEs, Africa, China, Nigeria, Cotonou, Accra

Spatial characteristics of the remotely-sensed surface urban heat island in Baton Rouge, LA: 1988-2003

Our understanding of urban effects on local climate remains unsatisfactory due to several difficulties: 1) the inherent complexity of the city-atmosphere system, 2) lack of a clear conceptual theoretical framework for inquiry, and 3) the high expense and enormous difficulties of acquiring a sufficient quantity of high-quality, high-resolution (both spatially and temporally) observations in cities. Using remotely-sensed data, this study analyzes urban heat islands (UHI) that are manifested through an elevation in the surface thermal emissions within urban regions known as surface heat islands (SHI). The study area for this research endeavor is Baton Rouge, Louisiana. Whereas the surface air temperature-derived UHI did not portray an accurate representation of distinct changes in surface temperature across the study area, the remotely-sensed surface temperature-derived SHI proved to reveal microscale differences that the surface air temperature-derived UHI was unable to depict. This study also provided verification that altering amounts of vegetation within a given land cover over time can reveal changes in surface temperature values, thus providing a means to reconstruct and predict future SHIs. This was achieved through regression equations predicting surface temperatures from known NDVI values. Finally, the moist static energy parameter was evaluated to test for a better indicator of the UHI over time throughout the study area. A decreasing temporal trend in MSE was identified throughout the study period (1988 - 2003) whereas no significant linear trend occurred in air temperature. This is supported by change detection rates generated from a comparison of the 1988 and 2003 LANDSAT data sets, as well as the range in 1988 and 2003 predicted surface temperatures (as a function of land cover)

Omnidirectional Information Gathering for Knowledge Transfer-based Audio-Visual Navigation

Audio-visual navigation is an audio-targeted wayfinding task where a robot agent is entailed to travel a never-before-seen 3D environment towards the sounding source. In this article, we present ORAN, an omnidirectional audio-visual navigator based on cross-task navigation skill transfer. In particular, ORAN sharpens its two basic abilities for a such challenging task, namely wayfinding and audio-visual information gathering. First, ORAN is trained with a confidence-aware cross-task policy distillation (CCPD) strategy. CCPD transfers the fundamental, point-to-point wayfinding skill that is well trained on the large-scale PointGoal task to ORAN, so as to help ORAN to better master audio-visual navigation with far fewer training samples. To improve the efficiency of knowledge transfer and address the domain gap, CCPD is made to be adaptive to the decision confidence of the teacher policy. Second, ORAN is equipped with an omnidirectional information gathering (OIG) mechanism, i.e., gleaning visual-acoustic observations from different directions before decision-making. As a result, ORAN yields more robust navigation behaviour. Taking CCPD and OIG together, ORAN significantly outperforms previous competitors. After the model ensemble, we got 1st in Soundspaces Challenge 2022, improving SPL and SR by 53% and 35% relatively.Comment: ICCV 202

Computational Anatomy for Multi-Organ Analysis in Medical Imaging: A Review

The medical image analysis field has traditionally been focused on the development of organ-, and disease-specific methods. Recently, the interest in the development of more 20 comprehensive computational anatomical models has grown, leading to the creation of multi-organ models. Multi-organ approaches, unlike traditional organ-specific strategies, incorporate inter-organ relations into the model, thus leading to a more accurate representation of the complex human anatomy. Inter-organ relations are not only spatial, but also functional and physiological. Over the years, the strategies 25 proposed to efficiently model multi-organ structures have evolved from the simple global modeling, to more sophisticated approaches such as sequential, hierarchical, or machine learning-based models. In this paper, we present a review of the state of the art on multi-organ analysis and associated computation anatomy methodology. The manuscript follows a methodology-based classification of the different techniques 30 available for the analysis of multi-organs and multi-anatomical structures, from techniques using point distribution models to the most recent deep learning-based approaches. With more than 300 papers included in this review, we reflect on the trends and challenges of the field of computational anatomy, the particularities of each anatomical region, and the potential of multi-organ analysis to increase the impact of 35 medical imaging applications on the future of healthcare.Comment: Paper under revie