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.     

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.     

A harmony search-based memetic optimization model for integrated production and transportation scheduling in MTO manufacturing

This paper investigates an integrated production and transportation scheduling problem in an MTO supply chain. A harmony search-based memetic optimization model is developed to handle this problem, in which certain heuristic procedures are proposed to convert the investigated problem into an order assignment problem. A novel improvisation process is also proposed to improve the optimum-seeking performance. The effectiveness of the proposed model is validated by numerical experiments. The experimental results show that (1) the proposed model can solve the investigated problem effectively and that (2) the proposed memetic optimization process exhibits better optimum-seeking performance than genetic algorithm-based and traditional memetic optimization processes.     

Optimal hedging through limit orders

This article applies the methods of stochastic dynamic programming to a risk management problem, where an agent hedges her derivative position by submitting limit orders. Therefore, this model is the first, in the literature on optimal trading with limit orders, to handle a problem of hedging options or other derivatives. A hedging strategy is developed where both the size and the limit price of each order is optimally set.     

Strategies for fostering basic psychological needs support in high quality youth leadership programs

Youth leadership programming has become an increasingly common context to foster basic psychological needs and promote youth development. The purpose of this qualitative study was to explore strategies involved in fostering youth needs support within six leadership programs. Two leaders and 30 youth participated in semi-structured interviews to better understand the strategies used to foster needs support. Findings revealed that leaders were able to foster a sense of relatedness among youth through building trusting adult-youth relationships and nurturing an inclusive environment. Maximizing choice and negotiating youth voice helped to foster youth’s autonomy. Finally, creating a task-oriented climate and providing intentional opportunities for skill-building helped to foster youth’s competence. Findings suggest that training for leaders is critical in understanding what, and how strategies should be employed to help foster youth needs support in leadership programming. Limitations and future directions are outlined.     

Optimizing global thermal coal shipments

Thermal coal is used to produce energy; with changing emissions standards and advents in renewable technology, the thermal coal market has seen significant transformation over the past decade. We develop a mixed-integer optimization problem that seeks to minimize shipment costs while meeting demand for thermal coal, and which respects quality constraints, supply limits, and port capacity; we use this model to analyze the following scenarios: (i) a counterfactual setting in which we compare historical shipping patterns to model results using a 2012 base year; (ii) the explicit effect of Chinese mandates on coal shipments; (iii) the impact on our shipping patterns of reduced Chinese and Indian demand; (iv) the effects of the Baltic Dry Index and oil prices; and (v) a comparison of shipments prior and subsequent to Panama Canal expansion. Our work can be used to inform policy, study responses to variable price and demand scenarios, and provide insight to both coal producers and consumers about the international coal market. For example, removal of mandates set by the Chinese government to fill its own demand decreases coal flows from Northern to Southern China by 56%, which has a spill-over effect on European and American markets; and, expansion of the Panama Canal leads to only modest shipping increases through the canal (6.7%), with more coal originating from Colombia serving Asian demand.     

Production and changeover control policies of a class of failure prone buffered flow-shops

This article deals with a stochastic optimal control problem for a class of buffered multi-parts flow-shops manufacturing system. The involved machines are subject to random breakdowns and repairs. The flow-shop under consideration is not completely flexible and hence requires setup time and cost in order to switch the production from a part type to another, this changeover is carried on the whole line. Our objective is to find the production plan and the sequence of setups that minimise the cost function, which penalises inventories/backlogs and setups. A continuous dynamic programming formulation of the problem is presented. Then, a numerical scheme is adopted to solve the obtained optimality conditions equations for a two buffered serial machines two parts case. A complete heuristic policy, based on the numerical observations which describe the optimal policies in system states, is developed. It will be shown that the obtained policy is a combination of a KANBAN/CONWIP and a modified hedging corridor policy. Moreover, based on our observations and existent research studies extension to cover more complex flow-shops is henceforth possible. The robustness of such a policy is illustrated through sensitivity analysis.     

汇编语言程序设计教学改革初探

汇编语言程序设计是计算机专业重要的基础课程,但由于其抽象、指令多等原因受到学生的忽视,实际教学效果很差。针对汇编语言程序设计的特点及目前教学现状,从改善教学效果和培养学生兴趣为出发点,对课程的教学内容、方法及手段进行探索,提高教学及实验效果,从而使汇编语言发挥其专业核心课的作用。     

Benefits of Hybrid Lateral Transshipments in Multi‐Item Inventory Systems under Periodic Replenishment

Lateral transshipments are a method of responding to shortages of stock in a network of inventory‐holding locations. Conventional reactive approaches only seek to meet immediate shortages. The study proposes hybrid transshipments which exploit economies of scale by moving additional stock between locations to prevent future shortages in addition to meeting immediate ones. The setting considered is motivated by retailers who operate networks of outlets supplying car parts via a system of periodic replenishment. It is novel in allowing non‐stationary stochastic demand and general patterns of dependence between multiple item types. The generality of our work makes it widely applicable. We develop an easy‐to‐compute quasi‐myopic heuristic for determining how hybrid transshipments should be made. We obtain simple characterizations of the heuristic and demonstrate its strong cost performance in both small and large networks in an extensive numerical study.     

Hard thresholding regression

In this paper, we propose the hard thresholding regression (HTR) for estimating high‐dimensional sparse linear regression models. HTR uses a two‐stage convex algorithm to approximate the ?₀‐penalized regression: The first stage calculates a coarse initial estimator, and the second stage identifies the oracle estimator by borrowing information from the first one. Theoretically, the HTR estimator achieves the strong oracle property over a wide range of regularization parameters. Numerical examples and a real data example lend further support to our proposed methodology.