物流配送系统中的运筹学问题及方法研究

物流配送系统中包含诸多运筹学问题,如配送中心选址中的0-1规划问题,货物配载中的背包问题,配送路线优化中的动态规划问题等,通过建立数学模型,利用运筹学方法与信息技术的结合可对上述问题加以解决,为配送业务的进一步发展提供帮助.     

Integrating uncertain user-generated demand data when locating facilities for disaster response commodity distribution

This paper presents a new facility location problem variant with application in disaster relief. The problem is unique in that both verified data and unverified user-generated data are available for consideration during decision making. The problem is motivated by the recent need of integrating unverified social data (e.g., Twitter posts) with data from more traditional sources, such as on-the-ground assessments and aerial flyovers, to make optimal decisions during disaster relief. Integrating social data can enable identifying larger numbers of needs in shorter amounts of time, but because the information is unverified, some of it may be inaccurate. This paper seeks to provide a “proof of concept” illustrating how the unverified social data may be exploited. To do so, a framework for incorporating uncertain user-generated data when locating Points of Distribution (PODs) for disaster relief is presented. Then, three decision strategies that differ in how the uncertain data is considered are defined. Finally, the framework and decision strategies are demonstrated via a small computational study to illustrate the benefits user-generated data may afford across a variety of disaster scenarios.     

Bayesian forecasting of UEFA Champions League under alternative seeding regimes

The evaluation of seeding rules requires the use of probabilistic forecasting models both for individual matches and for the tournament. Prior papers have employed a match-level forecasting model and then used a Monte Carlo simulation of the tournament for estimating outcome probabilities, thus allowing an outcome uncertainty measure to be attached to each proposed seeding regime, for example. However, this approach does not take into account the uncertainty that may surround parameter estimates in the underlying match-level forecasting model. We propose a Bayesian approach for addressing this problem, and illustrate it by simulating the UEFA Champions League under alternative seeding regimes. We find that changes in 2015 tended to increase the uncertainty over progression to the knock-out stage, but made limited difference to which clubs would contest the final.     

Small system dynamics model for alleviating the general practitioners rural care gap in Ontario,Canada

The disproportionate concentration of healthcare professionals in urban areas is a concern in many countries, including Canada. A need to address this rural care gap has driven a large number of government led initiatives worldwide over the years. This paper presents a model that can be used as a tool to examine the efficacy of such policies on the workforce distribution in the long term. A small system dynamics model is employed to simulate the current and future distribution of general physicians at a jurisdictional level. The model represents the transition of general practitioners to provide insight into the dynamics of care provision over time. The movement, and competition, between rural and urban areas is modeled to enable detailed exploration of the ability for proposed measures to alleviate the care gap in the future. Among the tested policies are such commonly used initiatives as financial incentives to rural professionals, promotion of medical education in rural areas, expansion of rural education programs and the engagement of international medical graduates etc. We demonstrate how the model can be used as a tool to determine an efficient and well-chosen combination of policies which can help alleviate the rural care gap in the future, given that some policies are more effective than others alone but also combined with other initiatives. The presented small system dynamics model is tested on Canada's reality, but its simple nature lends itself to easy application to other countries that experience a similar problem.     

基于二维码技术的烟草商业企业资产动态管理研究

本文基于烟草商业企业资产管理实际,探索二维码技术结合移动智能终端实现企业资产动态可视化管理模式,按照资产生命周期管理思想,提出"资产信息化管理的关键在于动态管理,核心是动态追踪"的资产管理新理念。     

The potty parity problem: Towards gender equality at restrooms in business facilities

In business facilities such as theaters, restaurants, stadiums, and etc., anecdotal evidences suggest that waiting lines for women's restrooms are longer than those for men's. Respectively, there have been growing concerns on ensuring restrooms in business facilities to be equally convenient for both women and men. This issue not only relates to gender equality, but also relates to business performance, since restroom experience directly affects performance efficiency (e.g., revenues, repeat sales, asset turnover, service times, and etc.). Nonetheless, current codes and legislations for designing restrooms in business facilities are not based on objective analyses but on the survey of experts that may be male biased. In this study, we develop a quantitative model using queueing theory and simulations to evaluate the waiting time for restrooms. Using our model, we compare the waiting times between women and men to examine if the current codes and legislations provide equal access. Our analysis reveals that the current standard specified by the Uniform Plumbing Code (UPC) still fails to achieve equal access. The methods demonstrated in this study may serve as a basis for design of restrooms in business facilities and improve both gender equality and performance efficiency in business facilities.     

Interdicting interdependent contraband smuggling,money and money laundering networks

This paper focuses on the problem of interdicting the interdependent contraband smuggling, money and money laundering (ICSML) networks of a transnational criminal organization (TCO). There are four interdependencies among these networks: money flows from the physical contraband smuggling network to the money network, monetary support from the money network flows to the smuggling network, money flows from the money network to the laundering network and incentives from the laundering network flow to the physical and money networks. The goal of the TCO is to maximize a (weighted) balance between the profit and scale of the contraband smuggling business. The goal of law enforcement is to minimize the best possible performance of the TCO. A bi-level integer programming model is built to address the two-player nature of this decision-making environment that specifically captures the interdependencies of the criminal networks. A dual-based reformulation is applied to address the bi-level problem. Case studies of applying this reformulation technique to realistic data sets are presented with a particular focus on understanding how inaccurate information about the structure of the ICSML networks impacts the performance of interdiction decisions. Sensitivity analysis is performed to analyze this impact by examining selected interdictions for perturbations of the network. Insights obtained include an understanding of effective interdiction policies for these types of networks and what type of information is most critical to capture in order to make effective interdiction decisions.     

Mathematical formulations for large scale check-in counter allocation problem

Strategic planning of check-in counter allocation with a focus on passenger waiting time is essential for airport operators to accommodate airline departures. This article proposes novel exact integer linear programming formulations for implementing first-in-first-out queue discipline, controlling waiting time and determining variable counter allocation with adjacency constraints for real world problems. Exact formulations in the existing literature handle small problems but do not address queue discipline and explicit control of waiting time. With our formulations, we solved live problems huge in size compared to those reported in the literature. The solutions are very efficient with passenger waiting times well below the international norms and high counter utilization.     

overview of OR techniques for airline revenue management

With the increasing interest in decision support systems and the continuous advance of computer science, revenue management is a discipline which has received a great deal of interest in recent years. Although revenue management has seen many new applications throughout the years, the main focus of research continues to be the airline industry. Ever since LITTLEWOOD (1972) first proposed a solution method for the airline revenue management problem, a variety of solution methods have been introduced. In this paper we give an overview of the solution methods presented throughout the literature.     

An empirical study on coalition formation and cost/savings allocation

Interest has been raised by the recent identification of potential savings through collaborative planning in logistics operations. Even though substantial savings can be realized, two key questions exist: (i) how should potential savings be divided among a group of collaborating companies and (ii) among potential collaborating companies, how should collaborating group(s) be formed? These two questions are studied in a specific context: among potential collaborating companies; a subset, denoted the leading companies, performs collaborative planning on behalf of the others and together, they initiate formation of a collaborating group. We use the concept of a business model to detail such context. Based on the literature on network formation where potential savings are modelled by a cooperative game, four business models are explored in four different subsets of leading companies. We propose a network model as a method to determine the stable collaborating group in each computation. A case study including eight forest companies is described and analyzed. Results show that very different solution characteristics can be achieved depending on the business model selected.