教学方法的多向度变革——《马克思主义基本原理概论》新教材教学法的研究与实践

为了创造性地贯彻《马克思主义基本原理概论》新教材的精神，课程组制定了“共性中创个性”的教学战略，在坚持共性、弘扬共性的基础上创造个性化教学特色，创造出了“坚持集体备课，鼓励多样化教学”的教学模式。     

货物运输车辆的调度算法

本文以上海煤炭公司为例,讨论了运煤车辆的计算机调度问题,提出一个数学模型及有效的近似算法。在算法实现中,采用了一些较为先进的数据结构,使运算速度及存储需求均有较大的改善。对实际算例计算结果表明,采用本算法进行运输车辆调度,经济效益比人工调度有明显的提高。     

Impact of investing in quality improvement on (Q,r, L) model involving the imperfect production process

This paper investigates the impact of quality improvement on the modified lot size reorder point models involving variable lead time and partial backorders. The formulated models include the imperfect production process and an investing option of improving the process quality. The objective is simultaneously optimizing the lot size, reorder point, process quality level and lead time. We first assume that the lead time demand follows a normal distribution, then relax this assumption to consider the distribution-free case where only the mean and standard deviation of lead time demand are known. An algorithm procedure of finding the optimal solution is developed, and two numerical examples are given to illustrate the results.     

The two-dimensional vector packing problem with piecewise linear cost function

The two-dimensional vector packing problem with piecewise linear cost function (2DVPP-PLC) is a practical problem faced by a manufacturer of children׳s apparel that ships products using courier service. The manufacturer must ship a number of items using standard-sized cartons, where the cost of a carton quoted by the courier is determined by a piecewise linear function of its weight. The cost function is not necessarily convex or concave. The objective is to pack all given items into a set of cartons such that the total delivery cost is minimized while observing both the weight limit and volume capacity constraints. This problem is commonly faced by many manufacturers that ship products using courier service. We formulate the problem as an integer programming model. Since the 2DVPP-PLC generalizes the classical bin packing problem, it is more complex and challenging. Solving it directly using CPLEX is successful only for small instances. We propose a simple heuristic that is extremely fast and produces high-quality solutions for instances of practical size. We develop an iterative local search algorithm to improve the solution quality further. We generate two categories of test data that can serve as benchmark for future research.     

一类特殊的有界变量目标规划的算法

对一类从m个决策变量中选择n(n≤m)个决策变量的有界变量目标规划问题,本文用0-1变量建立了它的数学模型,并提出了一种目标规划分层序列的改进算法及一种启发式算法。     

问题解决法在“电路CAD”课程教学中的应用

＂电路CAD＂是一门实践性很强的课程,授课老师应以如何提高学生的学习兴趣与学习效果为教学目标。问题解决法是指在教学过程中以＂围绕实践、重在应用＂为原则,引导学生带着问题去学习的启发式教学方法,该教学方法可以激发学生联系实际中有趣的现象,理解所学知识间的内在联系,探索问题的解决方案。通过问题解决法在＂电路CAD＂教学中的应用,调动了学生的学习积极性,优化了课堂教学,提高了教学效果,是一种适合在＂电路CAD＂教学中使用的方法。     

A reactive tabu search algorithm for the vehicle routing problem with simultaneous pickups and deliveries

The vehicle routing problem with pickups and deliveries (VRPPD) extends the vehicle routing problem (VRP) by allowing customers to both send and receive goods. The main difficulty of the problem is that the load of vehicles is fluctuating rather than decreasing as in the VRP. We design a reactive tabu search metaheuristic that can check feasibility of proposed moves quickly and reacts to repetitions to guide the search. Several new best solutions are found for benchmark problems.     

An investigation into the vehicle routing problem with time windows and link capacity constraints

In this work, we investigate a new, yet practical, variant of the vehicle routing problem called the vehicle routing problem with time windows and link capacity constraints (VRPTWLC). The problem considers new constraints imposed on road links with regard to vehicle passing tonnage, which is motivated by a business project with a Hong Kong transportation company that transports hazardous materials (hazmats) across the city and between Hong Kong and mainland China. In order to solve this computationally challenging problem, we develop a tabu search heuristic with an adaptive penalty mechanism (TSAP) to help manage the company's vehicle fleet. A new data set and its generation scheme are also presented to help validate our solutions. Extensive computational experiments are conducted, showing the effectiveness of the proposed solution approach.     

Point‐of‐Use Hybrid Inventory Policy for Hospitals

Modern point‐of‐use technology at hospitals has enabled new replenishment policies for medical supplies. One of these new policies, which we call the hybrid policy, is currently in use at a large U.S. Midwest hospital. The hybrid policy combines a low‐cost periodic replenishment epoch with a high‐cost continuous replenishment option to avoid costly stockouts. We study this new hybrid policy under deterministic and stochastic demand. We develop a parameter search engine using simulation to optimize the long‐run average cost per unit time and, via a computational study, we provide insights on the benefits (reduction in cost, inventory, and number of replenishments) that hospitals may obtain by using the hybrid policy instead of the commonly used periodic policies. We also use the optimal hybrid policy parameters from the deterministic analysis to propose approximate expressions for the stochastic hybrid policy parameters that can be easily used by hospital management.