一种解决配送规划问题的改进节约算法

车辆优化调度问题（VSP）是物流配送中广泛存在的一类问题，VSP问题属于NP一困难问题。在描述了简单VSP模型的基础上，对启发式算法中的C-W节约算法进行改进，将AK算法的思想运用其中，使计算结果的优化程度明显提高。     

A heuristic approach for solving an integrated gate reassignment and taxi scheduling problem

Capacity limitation of airport ground operation is one of the major limiting factors in air traffic operation. The congestion on the gate and taxiway causes severe delay and propagate effect on the flight schedule. This paper considers the problem of integrated gate reassignment and taxiway scheduling, in which complex constraints related to runway restriction, gate allocation and taxiway conflict are all incorporated when determining the schedule. To solve this problem, we propose a novel heuristic approach. First, all possible aircraft schedules are enumerated by disretizing the waiting time along the path. Then, the cost is evaluated for each schedule and the conflict detection is conducted to generate constraint sets. Finally, we propose a set partition model, in which each decision variable denotes a candidate schedule that takes into account the possible constraints when generated. This method is compared with a sequential method that solves gate reassignment and taxiway scheduling problem separately. Computational results highlight the strength of our method.     

顾客需求变化对供应商选择影响的一种量化方法

本文在零部件供应商参与产品设计的背景下,根据顾客需求权重的变化,利用QFD技术中的产品规划质量屋、部件配置质量屋及两者之间的关系,以客户满意度最大化为尺度,建立整数数学规划模型,求解各部件的变化情况,实现了从顾客需求变化到外包给供应商部件变化的转换,从而为供应商的动态选择提供依据,并给出了数值实例。     

Locating drivers in a trucking terminal network

We consider the problem of determining the home locations, or domiciles, of truck drivers for a less-than-truckload carrier. Domiciling decisions are complex, in part due to regulations and union rules restricting driver schedules, but have a significant impact on the operating costs of less-than-truckload carriers. We present an iterative scheme, using driver dispatch technology in each iteration, to allocate drivers to terminals and to determine drivers’ bids so as to satisfy union requirements. Computational experiments demonstrate the value of the iterative scheme and quantify the impact of union rules on the number of drivers required (and the resulting operating costs).     

On the short-maturity behaviour of the implied volatility skew for random strike options and applications to option pricing approximation

In this paper, we propose a general technique to develop first- and second-order closed-form approximation formulas for short-maturity options with random strikes. Our method is based on a change of numeraire and on Malliavin calculus techniques, which allow us to study the corresponding short-maturity implied volatility skew and to obtain simple closed-form approximation formulas depending on the derivative operator. The numerical analysis shows that these formulas are extremely accurate and improve some previous approaches for two-asset and three-asset spread options such as Kirk’s formula or the decomposition method presented in Alòs et al. [Energy Risk, 2011, 9, 52–57]. This methodology is not model-dependent, and it can be applied to the case of random interest rates and volatilities.     

Shift designs for freight handling personnel at air cargo terminals

This paper presents an integrated mixed integer linear programming (MILP) model for determining manpower requirements and related personnel shift designs for the build-up and break-down of the unit load devices (ULDs) at the air cargo terminal to minimize manpower costs. To utilize the manpower resources efficiently, we implement a new mechanism for demand leveling. In addition, we consider the qualification hierarchy between build-up and break-down workers. A case study based on the real-life data shows that the model is useful for manpower planning at air cargo terminals and the integrated approach is far superior to a traditional two-stage approach.     

Managing demand uncertainty through order overplanning

Most techniques for managing demand uncertainty require a certain degree of stability in the environment, since they are completely or partially based on the observation of historical data. When applied to a context characterized by irregular and sporadic demand these techniques show poor performances. In fact, in such a case uncertainty management calls for the gathering of information that directly anticipates future requirements. Although contexts with irregular and sporadic demand have received only minor attention in the past, they are currently gaining ever more importance and extending their occurrence. This paper illustrates and discusses a method, called order overplanning, specifically designed to cope with uncertainty in these environments. It consists of an articulate and coherent set of forecasting procedures, planning principles and slack control techniques. From a Master Production Scheduling (MPS) perspective, order overplanning is similar to hedging and option overplanning: gross requirements are larger than expected demand. The major difference is that order overplanning uses two distinct units in the MPS and forecasting procedures: while the MPS unit is an end item or a module, the forecasting unit is a customer order. This makes order overplanning able to exploit early information generated by each customer during its purchasing process, information that otherwise would be lost. This marked advantage comes to the detriment of an increased effort of integration between Sales and Manufacturing, especially for controlling the slack created to handle uncertainty.The paper first infers the principles and procedures of order overplanning by analysing the case study of an Italian telecommunications manufacturer. Then, it discusses the main advantages and disadvantages of this method, in order to identify the main factors affecting its performances and to determine the planning environments where it fits coherently.     

A local search algorithm for the optimization of the stochastic economic lot scheduling problem

This paper describes a model for the stochastic economic lot scheduling problem (SELSP) and a Local Search heuristic to find close to optimal solutions to this model. The SELSP considers multiple products, which have to be scheduled on a single facility with limited capacity and significant setup times and costs. The demand is modeled as a stationary compound renewal process. The objective is to find a schedule that minimizes the long-run average costs for setups and inventories while satisfying a given fill rate. We use a cyclic scheduling approach in which the individual cycle time of each product is a multiple of some basic period (fundamental cycle).For the deterministic version of the SELSP, efficient heuristics have been developed which guarantee the feasibility of the solution by adding an additional constraint to the problem. In our case this is not sufficient, because for the calculation of the average inventory levels and fill rates we need to develop a schedule with detailed timing of the lots. We present an efficient heuristic for this scheduling problem, which can also be used to check the feasibility of the solution. Thereby, the most time-consuming step (the calculation of average inventory levels and fill rates) is only performed for a limited set of candidates.The algorithm was tested on deterministic benchmark problems from literature and on a large set of stochastic instances. We report on the performance of the heuristic in both cases and try to identify the main factors influencing the objective.     

基于专家系统的自动化立体仓库出入库调度研究

通过对自动化立体仓库作业调度和货位分配原则的归纳总结，建立了专家系统的知识库：在此基础上，根据知识库的特征及立体仓库出入库调度的特点，建立了相应的推理机制；最后通过计算机算例仿真，探讨了专家系统在立体仓库调度中应用的可行性。     

具有模糊加工时间的Flexible Job-Shop Scheduling问题的研究

采用梯形模糊数来表征柔性生产系统中的时间参数,并在此基础上对具有模糊加工时间的柔性作业车间最小化制造跨度调度问题进行了描述。然后给出了基于粒子群优化的柔性作业车间调度模型。最后通过实例验证了模型的有效性。