Mixed integer (0–1) fractional programming for decision support in paper production industry

This paper presents an effective and efficient method for solving a special class of mixed integer fractional programming (FP) problems. We take a classical reformulation approach for continuous FP as a starting point and extend it for solving a more general class of mixed integer (0–1) fractional programming problems.To stress the practical relevance of the research we focus on a real-life application in paper production industry. The constantly advancing physical knowledge of large scale pulp and paper production did have a substantial impact on an existing DSS in which mixed integer (0–1) fractional programming is introduced. We show that the motivation to solve a real-life fractional programming problem can provide the basis for a new approach in a new context that has an added value of its own, even outside the given application area. We describe the main characteristics of the DSS, the necessity to develop a non-iterative solution procedure and demonstrate both the effectiveness and efficiency of the proposed approach from practical data sets.     

Staff rostering in call centers providing employee transportation

We address the staff rostering problem in call centers with the goal of balancing operational cost, agent satisfaction and customer service objectives. In metropolitan cities such as Istanbul and Mumbai, call centers provide the transportation of their staff so that shuttle costs constitute a significant part of the operational costs. We develop a mixed integer programming model that incorporates the shuttle requirements at the beginning and end of the shifts into the agent-shift assignment decisions, while considering the skill sets of the agents, and other constraints due to workforce regulations and agent preferences. We analyze model solutions for a banking call center under various management priorities to understand the interactions among the conflicting objectives. We show that considering transportation costs as well as agent preferences in agent-shift assignments provides significant benefits in terms of both cost savings and employee satisfaction.     

An integrated approach for water resources decision making under interactive and compound uncertainties

In recent years, the issue of water allocation among competing users has been of great concern for many countries due to increasing water demand from population growth and economic development. In water management systems, the inherent uncertainties and their potential interactions pose a significant challenge for water managers to identify optimal water-allocation schemes in a complex and uncertain environment. This paper thus proposes a methodology that incorporates optimization techniques and statistical experimental designs within a general framework to address the issues of uncertainty and risk as well as their correlations in a systematic manner. A water resources management problem is used to demonstrate the applicability of the proposed methodology. The results indicate that interval solutions can be generated for the objective function and decision variables, and a number of decision alternatives can be obtained under different policy scenarios. The solutions with different risk levels of constraint violation can help quantify the relationship between the economic objective and the system risk, which is meaningful for supporting risk management. The experimental data obtained from the Taguchi's orthogonal array design are useful for identifying the significant factors affecting the means of total net benefits. Then the findings from the mixed-level factorial experiment can help reveal the latent interactions between those significant factors at different levels and their effects on the modeling response.     

Incorporating balance concerns in resource allocation decisions: A bi-criteria modelling approach

We consider resource allocation problems where inputs are allocated to different entities such as activities, projects or departments. In such problems a common goal is achieving a desired balance in the allocation over different categories of the entities. We propose a bi-criteria framework for trading balance off against efficiency. We define and categorise indicators based on balance distribution and propose formulations and solution algorithms which provide insight into the balance-efficiency tradeoff. We illustrate our models by applying them to the data of a portfolio selection problem faced by a science funding agency and to randomly generated large-sized problem instances to demonstrate computational feasibility.     

An access network design problem with end-to-end QoS constraints

In this paper, we present an access network design problem with end-to-end quality of service (QoS) requirement. The problem can be conceptualized as a two-level hierarchical location-allocation problem on the tree topology with nonlinear side constraints. The objective function of the nonlinear mixed integer programming model minimizes the total cost of switch and fiber cable, while satisfying demand within the prescribed level of QoS. By exploiting the inherent structure of the nonlinear QoS constraints, we develop linearization techniques for finding an optimal solution. Also, we devise an effective exact optimal algorithm within the context of disjunctive constraint generation. We present promising computational results that demonstrate the effectiveness of the proposed solution procedure.     

Integrated retail decisions with multiple selling periods and customer segments: Optimization and insights

Integrating retail decisions on such aspects as assortment, pricing, and inventory greatly improves profitability. We examine a multi-period selling horizon where a retailer jointly optimizes assortment planning, pricing, and inventory decisions for a product line of substitutable products, in a market with multiple customer segments. Focusing on fast-moving retail products, the problem is modeled as a mixed-integer nonlinear program where demand is driven by exogenous consumer reservation prices and endogenous assortment and pricing decisions. A mixed-integer linear reformulation is developed, which enables an exact solution to large problem instances (with up to a hundred products) in manageable times. Empirical evidence is provided in support of a classical deterministic maximum-surplus consumer choice model. Computational results and managerial insights are discussed. We find that the optimal assortment and pricing decisions do not exhibit a simple, intuitive structure that could be analytically characterized, which reflects the usefulness of optimization approaches to numerically identify attractive trade-offs for the decision-maker. We also observe that suboptimal inventory policies significantly decrease profitability, which highlights the importance of integrated decision-making. Finally, we find that the seasonality of consumer preferences and supply costs present an opportunity for boosting the profit via higher inventory levels and wider assortments.     

民族地区教师教育模式创新与教师教育专业化

通过对教师教育性质的认识,结合四川西部民族地区教师专业化发展的现状及教师教育专业化过程中的问题,探讨了民族地区教师教育的理念,提出了民族地区教师教育人才培养新模式,对促进民族地区教师专业化发展及教师教育专业化可持续发展有着新的实践意义。     

教育哲学的大趋势——主体性教育

主体性教育是一种教育观念：它认为现代教育是以对真、善、美的追求为理想,以对受教育者的主体性的确认为依靠,以受教育者能动性和创造性的开发为核心,致力于促进人的主体性发展的教育。     

论程序设计类精品课程建设

精品课程建设是高等学校教学质量与教学改革工程中重要的项目之一。文章介绍了国家精品课程建设的宗旨和精品课程评审的指标体系,并着重从教学团队、教学内容、教学条件、教学方法与手段、教学效果、政策支持等方面讨论了程序设计类精品课程建设的具体措施。