Robust portfolio planning in the presence of market anomalies

In this study, a short-term portfolio modeling formulation is developed using existing anomalies as a single determinant for daily Istanbul Stock Exchange National 100 Composite Index (ISE) and US dollars (USD) returns in a Robust optimization (RO) framework. Using anomalies in planning within an RO framework establishes a balance between risk seeking and risk averse behaviors, as generating profit from anomalies is risky and RO enables to settle down the extreme risk seeking behavior. Applications of the model using various data sets result in real profit generation such that terminal wealth figures increase considerably more than Wholesale Price Index (WPI). This study demonstrates that RO is a viable approach to make use of anomaly information for short-term profits.     

An interactive three-stage model for mutual funds portfolio selection

The aim of this work is to be a useful instrument for helping finance practitioners on the selection of suitable mutual fund portfolios. The portfolio selection problem is characterized by imprecision and/or vagueness inherent in the required data and more generally, in the context where investors have to make decisions. In order to mitigate these problems, a three stage model has been proposed based on a multi-index model and considering several market scenarios described in an imprecise way by an expert. The proposed fuzzy model allows the Decision Maker to select, by means of an outranking method, a suitable portfolio taking into account the uncertainty related to the market scenarios and the imprecision and/or vagueness associated with the model data.     

The wireless network jamming problem

In adversarial environments, disabling the communication capabilities of the enemy is a high priority. We introduce the problem of determining the optimal number and locations for a set of jamming devices in order to neutralize a wireless communication network. This problem is known as the wireless network jamming problem. We develop several mathematical programming formulations based on covering the communication nodes and limiting the connectivity index of the nodes. Two case studies are presented comparing the formulations with the addition of various percentile constraints. Finally, directions of further research are addressed.     

考虑线下权力结构的制造商线上销售模式选择研究

在线下垂直实力对等、制造商主导和实体店主导三种渠道权力结构下，构建制造商、实体店和电商之间的博弈模型，探讨线下渠道权力结构与制造商线上销售模式的匹配关系。研究结果表明：（1）当电商要求的佣金比例较小时，在不同的线下渠道权力结构下，制造商都应该选择线上代销模式；而当电商要求的佣金比例较大时，在线下垂直实力对等结构下，制造商应该选择线上转销模式，而在制造商主导和实体店主导结构下，制造商应该选择线上代销模式。（2）当制造商选择线上转销模式时，在线下制造商主导的结构下，制造商给予实体店的批发价格最大，在垂直实力对等结构下次之，在实体店主导结构下最小。然而，线下渠道权力结构的差异并不会影响制造商给予电商的批发价格。（3）当制造商选择线上代销模式时，在线下制造商主导结构下，线下销售价格最高；在线下垂直实力对等结构下，线上销售价格最高。     

利用和声分散搜索算法解决动态共乘的乘客选择研究

动态共乘作为一种配合解决城市交通出行难题的新模式近年来引起了人们越来越多的关注，然而在较大范围内选择合适的乘客，以便获得最佳的综合服务效果却具有相当大的挑战性。本文正是针对这一问题，建立了以乘客效用最大化和司机总行程最短为目标函数，以满足司机与乘客的时间要求和司机参与约束为限制条件的多目标0-1规划共乘模型，用于帮助司机选择最合适的乘客。根据该模型的特点，构造了加入了分散搜索机制的新的和声搜索算法。在仿真实验时，针对司机和乘客效用的两种产生方式，在较大规模的路网环境下利用该算法分别对模型进行了求解，得到了Pareto最优解集。仿真结果不仅表明了模型的合理性和算法的可行性，而且还指出基于效用函数可以发现更多合适的潜在乘客。最后，通过与文献中其它算法的对比进一步展示了本文算法的有效性。     

Performance of TOC based finite capacity material requirement planning system for a multi-stage assembly factory

This paper aims to develop a finite capacity material requirement planning (FCMRP) system based on TOC philosophy (TOC-MRP) for multi-stage assembly factory that has some bottleneck stations. The proposed TOC-MRP system tries to load and schedule operations on bottleneck stations in a manner that they are free of idle time and overtime. The schedules on non-bottleneck stations will be arranged until they are not conflicting with those on the bottleneck stations. The non-bottleneck stations are allowed to have idle time and overtime if necessary. To analyse whether TOC-MRP is effective, it is compared with a FCMRP method that does not adopt TOC philosophy. The experimental results reveal that the TOC-MRP outperforms the FCMRP without TOC philosophy.     

Flexible Copula Density Estimation with Penalized Hierarchical B‐splines

The paper introduces a new method for flexible spline fitting for copula density estimation. Spline coefficients are penalized to achieve a smooth fit. To weaken the curse of dimensionality, instead of a full tensor spline basis, a reduced tensor product based on so called sparse grids (Notes Numer. Fluid Mech. Multidiscip. Des., 31, 1991, 241‐251) is used. To achieve uniform margins of the copula density, linear constraints are placed on the spline coefficients, and quadratic programming is used to fit the model. Simulations and practical examples accompany the presentation.     

非计算机专业“计算机程序设计”课程教学调查与思考

针对高校非计算机专业学生“计算机程序设计”课程分析教学方面存在的问题，指出非计算机专业程序设计课程教学模式改革，需要避免教学目标单一性，加强相关专业的结合，创新教学手段。     

A Multi-Dimensional Conceptual Framework for Trauma-Informed Practice in Addictions Programming

Previous research has conceptualized trauma-informed practice in relation to five key values: safety, trust, choice, collaboration, and empowerment. This research identifies key organizational, programmatic, and interpersonal characteristics in community-based residential addictions treatment programming that exemplify each of these principles. Utilizing qualitative research methods, involving open-ended, one to one interviews with clients in residential substance misuse treatment (n = 41), respondents identified the importance of experiencing “safety” in relation to physical safety, confidentiality, reassurance, rule enforcement, and peer relationships. “Trust” was manifested in sharing, staff availability, nonjudgmental interactions, positive relationship dynamics, and caring. “Choice” was articulated in relation to individual needs, participation, opportunities, and focus of efforts. “Collaboration” was characterized in relation to opportunities for feedback, planning, goal setting, specificity, and support. Finally, “empowerment” was characterized by comfort in sharing, trigger management, trauma awareness, and understanding. The findings provide a conceptual framework for a trauma-informed social services organizational practice environment. Findings can inform adaptations to social service delivery processes and programs to become aligned with the values of trauma-informed practice. Future research can build on this framework by testing the study findings with quantitative methods along with replicating current methods in other social service delivery sectors.     

The Value of Weather Information for E‐Commerce Operations

To be efficient, logistics operations in e‐commerce require warehousing and transportation resources to be aligned with sales. Customer orders must be fulfilled with short lead times to ensure high customer satisfaction, and the costly under‐utilization of workers must be avoided. To approach this ideal, forecasting order quantities with high accuracy is essential. Many drivers of online sales, including seasonality, special promotions and public holidays, are well known, and they have been frequently incorporated into forecasting approaches. However, the impact of weather on e‐commerce operations has not been rigorously analyzed. In this study, we integrate weather data into the sales forecasting of the largest European online fashion retailer. We find that sunshine, temperature, and rain have a significant impact on daily sales, particularly in the summer, on weekends, and on days with extreme weather. Using weather forecasts, we have significantly improved sales forecast accuracy. We find that including weather data in the sales forecast model can lead to fewer sales forecast errors, reducing them by, on average, 8.6% to 12.2% and up to 50.6% on summer weekends. In turn, the improvement in sales forecast accuracy has a measurable impact on logistics and warehousing operations. We quantify the value of incorporating weather forecasts in the planning process for the order fulfillment center workforce and show how their incorporation can be leveraged to reduce costs and increase performance. With a perfect information planning scenario, excess costs can be reduced by 11.6% compared with the cost reduction attainable with a baseline model that ignores weather information in workforce planning.