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.     

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。     

物流配送运输计算机调度系统设计研究

提出了开发计算机配送调度系统的设想。根据实际物流配送业务特点对配送运输计算机优化调度系统进行了初步设计。     

物流配送中心作业流程的统筹优化

针对物流配送中心成本压缩的现实问题，从配送中心内部作业优化的可挖掘潜力入手，对配送中心物流作业流程和作业时序进行了详细分析，并在此基础上运用运筹学方法中的关键路线法探讨了配送中心内部作业优化问题。     

Disaggregate spatio-temporal assessments of population exposure to aircraft noise

Estimates of exposure to aircraft noise are generally based on an average day of operations and residential population figures. While providing a convenient way to condense information, this does not reflect noise experiences across the day. This paper details an approach to inject more reality into exposure assessments, using disaggregate geographic information systems-based flight movement data and a procedure to track the population over the day. Using empirical evidence from Sydney, this leads to markedly different insights about noise impacts, which in turn has ramifications for policy-makers planning flight operations and residential settlement patterns in impacted areas.     

小型梯级水电站群优化调度损益计算及利益分配研究

在剖析利益分配机理的基础上,以龙岩区域小型水电站群历史数据为依据,基于粒子群算法构建水电站群利益损益计算模型和利益分配模型并进行分配系数计算。计算结果表明,该分配机制能激励各水电站积极参与联合调度,使水资源得到合理利用。     

基于碳排放量的机型排班优化

绿色低碳是当今的发展要求。航空公司可以从优化机型排班工作作为突破口,实现减少碳排放量的目的。为计算多条航班计划碳排放量,采用国际民用航空组织(ICAO)碳排放量计算公式,针对某航A320和B737两种机型,以碳排放量最小为约束条件,使用CPLEX软件求出某个航段上机型的最优解,最终实现整个航段的碳排放量最小。结果显示,在航段上使用两种混合机型比使用单一机型可节约更多的碳排放量,碳排放的减少区间为0.6%～2.9%,证明从碳排放量优化航空公司机型具备一定的合理性。     

Logistics scheduling to minimize inventory and transport costs

We study a logistics scheduling problem where a manufacturer receives raw materials from a supplier, manufactures products in a factory, and delivers the finished products to a customer. The supplier, factory and customer are located at three different sites. The objective is to minimize the sum of work-in-process inventory cost and transport cost, which includes both supply and delivery costs. For the special case of the problem where all the jobs have identical processing times, we show that the inventory cost function can be unified into a common expression for various batching schemes. Based on this characteristic and other optimal properties, we develop an O(n) algorithm to solve this case. For the general problem, we examine several special cases, identify their optimal properties, and develop polynomial-time algorithms to solve them optimally.