Integer linear programming formulation of the material requirements planning problem

Lot sizing procedures for discrete and dynamic demand form a distinct class of inventory control problems, usually referred to asmaterial requirements planning. A general integer programming formulation is presented, covering an extensive range of problems: single-item, multi-item, and multi-level optimization; conditions on lot sizes and time phasing; conditions on storage and production capacities; and changes in production and storage costs per unit. The formulation serves as a uniform framework for presenting a problem and a starting point for developing and evaluating heuristic and tailor-made optimum-seeking techniques.     

Facility location models for planning a transatlantic communications network

This paper presents two facility location models for the problem of determining how to optimally serve the requirements for communication circuits between the United States and various European and Middle Eastern countries. Given a projection of future requirements, the problem is to plan for the economic growth of a communications network to satisfy these requirements. Both satellite and submarine cable facilities may be used. The objective is to find an optimal placement of cables (type, location, and timing) and the routing of individual circuits between demand points (over both satellites and cables) such that the total discounted cost over a T-period horizon is minimized. This problem is cast as a multiperiod, capacitated facility location problem. Two mathematical models differing in their provisions for network reliability are presented. Solution approaches are outlined and compared by means of computational experience. Use of the models both in planning the growth of the network and in the economic evaluation of different cable technologies is also discussed.     

Balancing capacity and lot sizes

In many companies there is an on-going discussion about capacity, capacity utilization and capital tied up in inventories. However, traditional models such as the EOQ model only include capacity considerations in the set-up cost, or in the cost of a replenishment order. This implies e.g. that they do not consider the set-up time as a capacity constraint. Furthermore, in these models the set-up cost is usually treated as a constant, even though the opportunity cost for capacity in general is dependent upon the capacity utilization.The purpose of this paper is to derive an analytical model for the balancing of capacity and lot sizes. The model includes costs for capacity, work-in-process (queueing, set-up, and processing time), and finished goods inventory. The total costs are minimized with respect to capacity. Then, the corresponding, recommended lot sizes are determined. The model was tested with data from a Swedish manufacturing company. The results turned out to coincide with experiences of the company in many important respects. The model offers production management an opportunity to discuss the relationship between capacity, work-in-process, and lot sizes.     

Heuristic optimization methods for motion planning of autonomous agricultural vehicles

In this paper, two heuristic optimization techniques are tested and compared in the application of motion planning for autonomous agricultural vehicles: Simulated Annealing and Genetic Algorithms. Several preliminary experimentations are performed for both algorithms, so that the best neighborhood definitions and algorithm parameters are found. Then, the two tuned algorithms are run extensively, but for no more than 2000 cost function evaluations, as run-time is the critical factor for this application. The comparison of the two algorithms showed that the Simulated Annealing algorithm achieves the better performance and outperforms the Genetic Algorithm. The final optimum found by the Simulated Annealing algorithm is considered to be satisfactory for the specific motion planning application.     

义工旅行动机的量表开发与验证

随着义工旅行在年轻人中的普及,不少义工组织、旅行社和旅游目的地纷纷推出义工旅行项目。然而目前的项目安排大多仿照国外,对国内年轻人的需求认识尚不明晰,学术界对这一主题的研究也相对匮乏。鉴于此,以Voluntour和EASIN义工旅行组织的参与者为研究对象,严格遵循量表开发的流程,采用探索性因子分析、3次验证性因子分析和结构方程模型检验的方法,从多个角度验证了量表的信度和效度,得到了基于中国情境的义工旅行动机量表。研究结果表明：(1）由4个维度17个测量项目组成的量表,整体结构良好,具有较好的稳定性和适用性,可成为义工旅行研究的有效测量工具;(2）义工旅行的动机维度可划分为休闲逃避、深度体验、自我服务/发展与利他四类,动机中的利他维度是区分义工旅行与背包旅行、打工度假旅行的关键属性,是年轻人选择深度休闲方式的一种体现;(3）与国外研究相比,基于中国情境的量表无保护功能与宗教参与的动机维度,且社交动机表现不突出。最后,探讨了义工旅行项目在产品开发和市场营销方面的策略。     

A model for the economic evaluation of master city plans: a pilot study of Västerås,Sweden

The paper introduces the framework, problems addressed, objective function, types of variables and so on for a model designed to facilitate the economic evaluation of master city plans. The model presented here has been used in a pilot study of the city of Västerås, Sweden. It consists of three main parts, data, results and method. Some conclusions are drawn.     

Improving biorefinery planning: Integration of spatial data using exact optimization nested in an evolutionary strategy

Biorefineries can provide a product portfolio from renewable biomass similar to that of crude oil refineries. To operate biorefineries of any kind, however, the availability of biomass inputs is crucial and must be considered during planning. Here, we develop a planning approach that uses Geographic Information Systems (GIS) to account for spatially scattered biomass when optimizing a biorefinery’s location, capacity, and configuration. To deal with the challenges of a non-smooth objective function arising from the geographic data, higher dimensionality, and strict constraints, the planning problem is repeatedly decomposed by nesting an exact nonlinear program (NLP) inside an evolutionary strategy (ES) heuristic, which handles the spatial data from the GIS. We demonstrate the functionality of the algorithm and show how including spatial data improves the planning process by optimizing a synthesis gas biorefinery using this new planning approach.     

In–Out Algorithm for assortment planning under a ranking-based consumer choice model

We consider a retailer’s assortment planning problem under a ranking-based consumer choice model. The retailer incurs a fixed carrying cost per product offered, a substitution penalty cost for each customer who does not purchase his first choice, and a penalty cost on lost sales. We develop an effective In–Out Algorithm to identify the optimal solution. The extensive numerical study shows that the algorithm performs well, and is more than 10,000 times faster than enumeration on problems with 20 products.     

长沙建设国家中心城市的对策研究

建设国家中心城市是长沙市近年的奋斗目标.长沙市怎样建设国家中心城市,可以从与国内其他国家中心城市的全面比照当中得到建设方案.一是从经济实力、产业结构、科教实力、金融行业发展、对外开放等代表城市综合实力的5个方面,二是从引领和辐射功能、集聚功能、物流枢纽功能等代表城市功能的3个方面,对长沙与国内5个国家中心城市(天津、重庆、成都、武汉、郑州)进行对比研究.通过对比,从国内5个国家中心城市的城市功能差别当中找准长沙的城市功能定位,从长沙市城市综合实力的差距和优劣势当中发现长沙建设国家中心城市所要解决的问题,为此提出长沙建设国家中心城市的建设对策.     

大数据背景下基于5S的城市交通拥堵评价模型研究

近几年来,城市交通拥堵问题日益突出,极大制约了城市发展。在大数据背景下,为了准确掌握交通实时拥堵状况,改善城市交通,便利市民出行,本文深入挖掘城市交通拥堵的影响因素,构建了基于交通5S要素的城市拥堵理论模型,运用径向基函数神经网络方法工具,以上海静安寺、上海站、陆家嘴周围三大拥堵路段的交通数据集为例,验证了该模型的有效性。实验结果表明,由该模型获得的城市交通拥堵预测值与上海实际交通路况具有较好的拟合效果,表明交通5S模型与方法能够准确有效地评价城市交通拥堵。