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In this article, we define two different workforce leveling objectives for serial transfer lines. Each job is to be processed on each transfer station for c time periods (e.g., hours). We assume that the number of workers needed to complete each operation of a job in precisely c periods is given. Jobs transfer forward synchronously after every production cycle (i.e., c periods). We study two leveling objectives: maximin workforce size () and min range (R). Leveling objectives produce schedules where the cumulative number of workers needed in all stations of a transfer line does not experience dramatic changes from one production cycle to the next. For and a two‐station system, we develop a fast polynomial algorithm. The range problem is known to be NP‐complete. For the two‐station system, we develop a very fast optimal algorithm that uses a tight lower bound and an efficient procedure for finding complementary Hamiltonian cycles in bipartite graphs. Via a computational experiment, we demonstrate that range schedules are superior because not only do they limit the workforce fluctuations from one production cycle to the next, but they also do so with a minor increase in the total workforce size. We extend our results to the m‐station system and develop heuristic algorithms. We find that these heuristics work poorly for min range (R), which indicates that special structural properties of the m‐station problem need to be identified before we can develop efficient algorithms. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 577–590, 2016 相似文献
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The warehouse problem with deterministic production cost, selling prices, and demand was introduced in the 1950s and there is a renewed interest recently due to its applications in energy storage and arbitrage. In this paper, we consider two extensions of the warehouse problem and develop efficient computational algorithms for finding their optimal solutions. First, we consider a model where the firm can invest in capacity expansion projects for the warehouse while simultaneously making production and sales decisions in each period. We show that this problem can be solved with a computational complexity that is linear in the product of the length of the planning horizon and the number of capacity expansion projects. We then consider a problem in which the firm can invest to improve production cost efficiency while simultaneously making production and sales decisions in each period. The resulting optimization problem is non‐convex with integer decision variables. We show that, under some mild conditions on the cost data, the problem can be solved in linear computational time. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 367–373, 2016 相似文献
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Robert Erdeniz 《Defence Studies》2016,16(3):248-269
Parts of NATO’s contemporary planning framework called the comprehensive operations planning directive (COPD), and parts of the operation-level planning process should be revised since they suffer from methodological inconsistency. This claim is defended by discussing contradicting methodological properties and heuristics applied when framing and managing a military problem in accordance with the COPD. The methodological inconsistency within the COPD; in other words, simultaneously applying contradictory methodological properties, implies one theoretical and three practical implications. The theoretical implication is summarised in a meta-theoretical framework and explained by discussing five methodological properties: non-linearity, emergence, independently changeable generalisations, invariance and boundaries. The three practical implications of methodology imply that methodology is guiding: the problem-frame, conceptual development and action. To improve military planners’ understanding and management of these four identified implications, NATO is recommended to develop a “handbook of methodology.” The purpose of such a handbook should be to emphasise the utility of methodology when planning military operations. 相似文献
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对敌防空压制(suppression of enemy air defenses, SEAD)场景是多无人机协同的典型应用,针对该场景特点,在任务规划问题基础上将各类型无人机数量也作为决策变量,充分表征目标、任务和无人机的多种约束,建立异构无人机编队路径问题模型。设计了双层联合优化方法求解该模型:上层设计了任务衔接参数指标,精确评估各类型无人机需求,指导无人机配置调整;下层设计了改进遗传算法,高效处理多类型约束并能结合无人机数量变化对任务方案进行精细调整;双层相互协调获得满足需求的无人机配置和执行方案。仿真结果表明,该方法可以在避免遍历无人机配置组合的前提下获得合理的无人机配置方案和高效可行的执行方案。 相似文献
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A mathematical formulation of an optimization model designed to select projects for inclusion in an R&D portfolio, subject to a wide variety of constraints (e.g., capital, headcount, strategic intent, etc.), is presented. The model is similar to others that have previously appeared in the literature and is in the form of a mixed integer programming (MIP) problem known as the multidimensional knapsack problem. Exact solution of such problems is generally difficult, but can be accomplished in reasonable time using specialized algorithms. The main contribution of this paper is an examination of two important issues related to formulation of project selection models such as the one presented here. If partial funding and implementation of projects is allowed, the resulting formulation is a linear programming (LP) problem which can be solved quite easily. Several plausible assumptions about how partial funding impacts project value are presented. In general, our examples suggest that the problem might best be formulated as a nonlinear programming (NLP) problem, but that there is a need for further research to determine an appropriate expression for the value of a partially funded project. In light of that gap in the current body of knowledge and for practical reasons, the LP relaxation of this model is preferred. The LP relaxation can be implemented in a spreadsheet (even for relatively large problems) and gives reasonable results when applied to a test problem based on GM's R&D project selection process. There has been much discussion in the literature on the topic of assigning a quantitative measure of value to each project. Although many alternatives are suggested, no one way is universally accepted as the preferred way. There does seem to be general agreement that all of the proposed methods are subject to considerable uncertainty. A systematic way to examine the sensitivity of project selection decisions to variations in the measure of value is developed. It is shown that the solution for the illustrative problem is reasonably robust to rather large variations in the measure of value. We cannot, however, conclude that this would be the case in general. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48: 18–40, 2001 相似文献
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The Selection Allocation Problem (SAP) is a single period decision problem which involves selecting profit‐maximizing (or cost‐minimizing) activities from various distinct groups, and determining the volume of those activities. The activities in each group are selected subject to the availability of that group's resource, which is provided by either pooling or blending raw inputs from several potential sources. Imbedded in the decision process is the additional task of determining how much raw input is to be allocated to each group to form the resource for that group. Instances of this problem can be found in many different areas, such as in tool selection for flexible manufacturing systems, facility location, and funding for social services. Our goal in this paper is to identify and exploit special structures in the (SAP) and use those structures to develop an efficient solution procedure. © 1999 John Wiley & Sons, Inc. Naval Research Logistics 46: 707–725, 1999 相似文献
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本文以中国学术期刊网收录的1637篇文献记录为分析对象,利用聚类分析、战略坐标分析和社会网络分析等方法,对国内语言规划与政策领域的主要研究方向、发展状态和核心作者群进行分析。研究结果表明,国内语言规划与政策研究主要涉及八个方向:少数民族语言研究、官方语言研究、语言态度研究、推广普通话研究、方言研究、外语研究、语言问题研究、语言文字规范研究。其中,少数民族语言研究、官方语言研究和方言研究处于领域核心且发展比较成熟。推广普通话研究也是领域关注的核心问题,但目前发展尚不成熟。相比之下,语言态度研究、外语研究、语言文字规范研究和语言问题研究相对处于领域边缘且尚不够成熟。围绕各个研究方向均已形成了较稳定的杰出作者群体,多数学者都反映出"多主题跟进、单主题深入"的研究模式。 相似文献
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