A multicriteria decision-making approach to university resource allocations and information infrastructure planning

This paper presents an application of zero-one goal programming (GP) as an aid for resource allocations for information infrastructure planning in a university. The GP model is developed and analyzed to address the dramatic growth in information technology use and network planning. The analytic hierarchy process method is used to assign proper weights to prioritized project goals. Sensitivity analyses are performed to improve the model applicability. The application of the GP model adds insight to the planning functions of the University's information systems.     

A practical prioritization by multi-level group decision support

Military capability is proposed to be defined according to the DYNPOT scoring method. Multiobjective resource allocation of shared resources by group decision-making can combine analytic and qualitative modeling. Recently it has been pointed out that the goal programming model is superior to other models though it remained to be answered how to take into account hierarchy of decision makers (and objectives) (Stummer and Vetschera in Cent Eur J Oper Res 11:3–260, 2003). In this article it is tried to present, that the quantitative model can be easily adapted to the qualitative STT/QFD model of objectives of top-level group of decision-makers. The subsequent phases of the qualitative and the analytic solution of a multiobjective cooperative resource allocation problem can be applied within the group decision-making framework of defence requirements capability-based planning.     

Implementation of goal programmingin long-range resource planning in university management

This paper presents a resource allocation model via Goal Programming (GP) in a long-range planning horizon in university management. In the proposed model, the introduction of new courses in the academic units and the allocation of available budget within the academic units as well as the forecast of the budget which is actually needed for better academic performance are taken into consideration. An illustrative example is presented to expound the model     

水资源配置方案综合评价中的信息损失测度研究

水资源配置的多属性特征使得在方案综合评价中依据不同的聚合方法,能够获得不完全一致的方案排序结果。本文从水资源配置方案评价的决策矩阵及方案排序结果中的信息量大小入手,利用信息熵理论和斯皮尔曼等级相关系数提出衡量水资源配置方案综合评价中信息损失的香农斯皮尔曼测度。并构造由2种权重(熵权法权重、证据理论权重)与3种评价模型(简单加权法、模糊优选法、TOPSIS)组合而成的6种综合评价模型。最后,将香农斯皮尔曼测度运用到天津市水资源配置方案综合评价过程中的信息损失的衡量,并与文献中的综合评价模型所得结果进行比较。结果表明,采用证据理论权重-模糊优选评价模型所得评价结果的绝对信息损失和相对信息损失最小。通过水资源配置方案综合评价中的信息损失测度研究,能够使得水资源配置方案综合评价过程更加透明,并为决策部门选取理想的水资源配置方案综合评价方法提供决策支持。     

A derivative-free approach for a simulation-based optimization problem in healthcare

Hospitals have been challenged in recent years to deliver high quality care with limited resources. Given the pressure to contain costs, developing procedures for optimal resource allocation becomes more and more critical in this context. Indeed, under/overutilization of emergency room and ward resources can either compromise a hospital’s ability to provide the best possible care, or result in precious funding going toward underutilized resources. Simulation-based optimization tools then help facilitating the planning and management of hospital services, by maximizing/minimizing some specific indices (e.g. net profit) subject to given clinical and economical constraints. In this work, we develop a simulation-based optimization approach for the resource planning of a specific hospital ward. At each step, we first consider a suitably chosen resource setting and evaluate both efficiency and satisfaction of the restrictions by means of a discrete-event simulation model. Then, taking into account the information obtained by the simulation process, we use a derivative-free optimization algorithm to modify the given setting. We report results for a real-world problem coming from the obstetrics ward of an Italian hospital showing both the effectiveness and the efficiency of the proposed approach.     

A Model of Vacancy Chains as a Mechanism for Resource Allocation

Vacancy chains can be tracked in any context where the availability of a desirable resource triggers a cascade of occupations through which the scarce resource flows through different owners. However, under certain conditions, vacancy chains, rather than markets or other forms of competition, determine the allocation of the resource. This article develops a formal and computational model of vacancy chains as a mechanism for resource allocation in order to find out their properties with respect to organizational forms.

We find that hierarchies with few middle managers are particularly prone to make use of vacancy chains in order to allocate resources that originate at the top, such as employment positions. In fact, vacancy chains often disappear when information is widely available, because information is likely to attract applicants who engage in a competition. Thus, the many middle managers of a thick organization may compete for a resource that originates at the top. On the contrary, organizations that are thick at the bottom and at the top, but thin in the middle, are most likely to regulate resource allocation by means of vacancy chains.     

An inexact-stochastic dual water supply programming model

This paper introduces an inexact-stochastic dual water supply programming (ISDWSP) model based on analysis of the inexact characteristics in demand and supply subsystems of dual water supply system and their dynamic interactions. The model is based on an inexact chance-constrained programming (ICCP) method allowing both distribution information in B (right parameter in the model constrain) and uncertainties in A (left parameter in the model constrain) and C (parameter in the model function) with objective of maximizing economic return, and constrained to available water resource, economical, environmental and social constrains. The decision-making variables of ISDWSP model are water demanded amount by different sectors and waterworks building scale. In the solution process, the ISDWSP is transformed into two deterministic sub-models, which correspond to the upper and lower bounds of the objective function, and the reasonable interval solution set in the given decision space can be obtained by solving the two sub-models. Thus, decision alternatives can be obtained by adjusting decision variable values within their solution intervals and will be useful for decision makers to choose the projected applicable conditions considering tradeoffs between eco-environmental and economic objectives. The model is also applied in a new developing zone of North China with the results of the case study providing reasonable solutions for dynamic planning of different source water (DSW) allocation in a regional system. Finally, waterworks building plan is generated based on the projected applicable conditions.     

Disaster preparedness in humanitarian logistics: A collaborative approach for resource management in floods

The logistical deployment of resources to provide relief to disaster victims and the appropriate planning of these activities are critical to reduce the suffering caused. Disaster management attracts many organisations working alongside each other and sharing resources to cope with an emergency. Consequently, successful operations rely heavily on the collaboration of different organisations. Despite this, there is little research considering the appropriate management of resources from multiple organisations, and none optimising the number of actors required to avoid shortages or convergence.This research introduces a disaster preparedness system based on a combination of multi-objective optimisation and geographical information systems to aid multi-organisational decision-making. A cartographic model is used to avoid the selection of floodable facilities, informing a bi-objective optimisation model used to determine the location of emergency facilities, stock prepositioning, resource allocation and relief distribution, along with the number of actors required to perform these activities.The real conditions of the flood of 2013 in Acapulco, Mexico, provided evidence of the inability of any single organisation to cope with the situation independently. Moreover, data collected showed the unavailability of enough resources to manage a disaster of that magnitude at the time. The results highlighted that the number of government organisations deployed to handle the situation was excessive, leading to high cost without achieving the best possible level of satisfaction. The system proposed showed the potential to achieve better performance in terms of cost and level of service than the approach currently employed by the authorities.     

基于“零和收益”的SBM效率分配方法及应用

在松弛变量度量(slacks-based measure,SBM)效率评价方法的基础上,首先明确投入(产出)要素固定的生产系统中,投入(产出)要素在各决策单元间的竞争性关系;然后采用比例分配策略对SBM无效决策单元的投入(产出)松弛进行效率分配,以构建一个基于零和收益的SBM(zero sum gains SBM,ZSG-SBM)效率分配方法;再通过分析ZSG-SBM模型与SBM模型效率评价结果的关系,给出了比例分配策略ZSG-SBM模型的求解方法;最后应用实例研究验证了本文模型在要素存在竞争性的复杂生产系统效率评价和资源分配中的优势。     

Adapting Multi-criteria Planning to the Nigerian Economy

Techniques of development planning involve physical and financial aspects. Financial planning refers to the allocation of monetary resources; in Nigeria the previous development plans and budgets, which had been based on the incremental approach, contained various shortcomings, resulting in the deliberate inflation of estimated expenditure, and consequently it has been associated with retarded growth and conflicts between ministries. In addition, the approach does not adequately relate national objectives to their priorities. Conventional mathematical programming models are unable to allocate resources effectively in a conflicting environment. This paper proposes a goal programming model for allocating a country's scarce resources among competing sectors during a planned period. The goal programming model is shown to be adequate for allocating resources under the conflicting conditions of national planning. The model can help to determine all the priorities for the goals.     

A genetic approach for strategic resource allocation planning

Enterprises often implement a measurement system to monitor their march towards their strategic goals. Although this way it is possible to assess the progress of each goal, there is no structured way to reconsider resource allocation to those goals and to plan an optimal (or near optimal) allocation scheme. In this study we propose a genetic approach to match each goal with an autonomous entity (agent) with a specific resource sharing behavior. The overall performance is evaluated through a set of functions and genetic algorithms are used to eventuate in approximate optimal behavior’s schemes. To outline the strategic goals of the enterprise we used the balanced scorecard method. Letting agents deploy their sharing behavior over simulation time, we measure the scorecard’s performance and detect distinguished behaviors, namely recommendations for resource allocation.     

Resource Analysis in Project Evaluation: A Multicriteria Approach

In this paper we develop and demonstrate the application of a goal programming model. It is designed to assist top management in incorporating organizational goals when allocating funds to competing projects. Investment decisions, however, normally involve several, often conflicting goals. The fact that some of these goals cannot be measured in dollars or other scales further complicates the problem. Among the many proposed methodologies of multicriteria decision-making (MCDM), goal programming (GP) is perhaps the most popular and widely used. It provides optimal solutions; however, it has a major drawback: the decision-maker must specify the goals and priorities a priori. To overcome this problem, we suggest the Delphi method, a systematic procedure to obtain a consensus from a group of participants. It is conducted prior to GP to (1) identify the goals, (2) determine priorities among the goals, and (3) establish a target level for each goal. To test the practicality and extent of applicability, the proposed model is directly applied to evaluate rural road projects of the Division of Transportation, Bureau of Indian Affairs (BIA), US Department of Interior.     

Centralized resource allocation DEA models based on revenue efficiency under limited information

In this paper, we extend the centralized DEA models by Lozano et al (2011) to allocate resources based on revenue efficiency across a set of DMUs under a centralized decision-making environment. The aim is to allocate resources so as to maximize the total output revenue produced by all the DMUs under limited information. To uncover the sources of total revenue increase from the centralized resource allocation model, we further decompose the aggregate revenue efficiency into three components: the aggregate output-oriented technical efficiency, the aggregate output allocative efficiency and the aggregate revenue re-allocative efficiency. Finally, two empirical data sets are presented to show that our proposed approach is not only an efficient tool to allocate the resources among the DMUs based on the revenue efficiency but additionally provides the central DM with guidance on how to identify the weak areas where more effort should be devoted to improve the total outputs.     

A decision tool for optimal irrigated crop planning and water resources sustainability

In the present study, the conjunctive use policies of surface and ground water resources are developed for minimizing water shortage in an irrigation district subject to constraints on groundwater withdrawals and crop planning capacities. An integrated soil water balance algorithm is coupled to a non-linear optimization model in order to carry out water allocation planning in complex deficit agricultural water resources systems based on an economic efficiency criterion. Various options of conjunctive use water resources along with current and proposed cropping patterns have been explored by Koohdasht Irrigation District (KID), a semi-arid region in I.R. Iran. The analysis provides various scenarios, which can help managers in decision-making for the optimum allocation plans of water resources within the irrigation area. The results reveal that the proposed model, as a decision tool for optimal irrigated crop planning and water resources sustainability, may be used for maximizing the overall net benefits and global water productivity of an irrigation district considering an allowable annual recharge of groundwater. Findings indicate the importance of the conjunctive water management modeling, which can be easily implemented and would enhance the overall benefits from cropping activities in the study area.     

网络信息系统中信息安全防御资源分配策略分析——基于约束理论视角

安全经济性是企业信息安全防御决策的重要依据,在网络信息系统中企业需要权衡如何在众多不同信息资源节点间实施防御资源的合理分配。本文首先构建了无安全资源约束下的安全防御决策模型,研究企业在信息安全防御中如何来优化分配其防御资源,得出不同信息节点存在防御阀值以及各节点的相对经济防御水平值;在此模型基础上增加了安全防御资源约束条件,分析不同信息资源节点的防御价值、损失预期、攻击概率等因素对决策的影响,得出企业在不同节点上的防御优先级以及防御过程中投入资源量等相关结论。     

Applications of resource assignment and scheduling with Petri Nets and heuristic search

This paper introduces a new Petri Net based approach for resource allocation and scheduling. The goals are (i) minimize the number of required resources given a set of jobs, (ii) find both an assignment for all jobs in the span of a predefined shift and (iii) the sequence in which such jobs are executed. The studied problem was inspired from a complex real life manufacturing shop as described in this document. The modeling of the processes and jobs is carried out with Petri Nets due to their capability of representing dynamic, concurrent discrete-event dynamic systems. The resource assignment starts with an initial feasible solution (initial number of resources) and then follows with a re-optimization process aimed to further reduce the resource requirements. The algorithm is based on a modified Heuristic Search method previously presented. The algorithm was tested first on a number of instances from the literature and then on the aforementioned system (a car seat cover manufacturer). The proposed approach shows not only good results in terms of performance but also shows the potential of Petri Nets for modeling and optimizing real-life systems. An implementation phase at the first stages of the process is underway at the time of writing.     

Optimal scheduling of batch industrial facilities

An increasing interest in batch processing has been evident in recent years. This renewed interest is explained by the inherent flexibility of such plants that permits a high level of response to uncertain market conditions and requirements. This level of response does require the use of efficient tools to help the decision-making process at the design and operational level. This paper presents a Mixed Integer Linear Program (MILP) model to optimise the scheduling of batch facilities subject to changeovers and distribution constraints so as to guarantee a pre-defined objective. Such an objective can be defined as the minimum orders' total lateness or the maximum distribution units loading capacity, among others. A continuous-time representation is used as well as the concept of job predecessor and successor to effectively handle changeovers. Facilities having non-identical parallel units/lines, sequence-dependent orders, finite release times for units and orders, restrictions on the suitability of jobs to lines/units and different possible destinations to available distribution units are also considered. Based on these characteristics the proposed model is able to determine the optimal allocation of jobs to production lines/units, the sequence of jobs on every line/unit and the starting and completion production times of each order. Also, the usage and allocation of the distribution resources (eg trucks) to orders and destinations are obtained based on their availability and suitability to the orders. The model led to the development of a prototype information system that can be used as a tool to help the decision-making process at the operational plant level.Finally, the applicability of the proposed system/formulation is shown through the resolution of an industrial real case where the production of polymers is performed.     

外源投入型两阶段制造系统网络DEA效率分析研究

制造过程评价是改善制造系统效率的重要一环,传统的评价方法将每个制造系统决策单元视为黑箱来研究整体效率,忽略了中间产品转化信息及投入要素在各子过程中的配置信息。针对两阶段(第二阶段有外源性新投入)制造系统的效率评估问题,分别在固定规模报酬和可变规模报酬假设下,充分利用制造系统中间产品的转化及外源投入要素的配置信息,建立了制造系统网络DEA效率测度及分解模型,建模方法遵循客观评价原则,无需事先主观确定子效率和系统效率之间的组合关系。并将其应用于钢铁制造系统效率测度与分解,研究结果表明该方法能够挖掘决策单元内部子单元的效率情况,帮助决策者发现复杂制造过程非有效的根源,为复杂制造过程的整体效率测度及分解提供了有效的分析方法。     

Cost-based decision-making in middleware virtualization environments

Middleware virtualization refers to the process of running applications on a set of resources (e.g., databases, application servers, other transactional service resources) such that the resource-to-application binding can be changed dynamically on the basis of applications’ resource requirements. Although virtualization is a rapidly growing area, little formal academic or industrial research provides guidelines for cost-optimal allocation strategies. In this work, we study this problem formally. We identify the problem and describe why existing schemes cannot be applied directly. We then formulate a mathematical model describing the business costs of virtualization. We develop runtime models of virtualization decision-making paradigms. We describe the cost implications of various runtime models and consider the cost effects of different managerial decisions and business factors, such as budget changes and changes in demand. Our results yield useful insights for managers in making virtualization decisions.     

Multi-objectives Tabu Search based algorithm for progressive resource allocation

Military course of action planning involves time and space synchronization as well as resource and asset allocation. A mission could be seen as a defined set of logical ordered tasks with time and space constraints. The resources to task rules require that available assets should be allocated to each task. A combination of assets might be required to execute a given task. The couple (task, resources) constitutes an action. This problem is formulated as a multi-objectives scheduling and resource allocation problem. Any solution is assessed based on a number of conflicting and heterogeneous objectives. In fact, military planning officers should keep perfecting the plan based on the Commander’s criteria for success. The scheduling problem and resource allocation problem are considered as NP-Hard Problems [A. Guitouni, B. Urli, J.-M. Martel, Course of action planning: A project based modelling, Working Paper, Faculté des sciences de l’ administration, Université Laval, Québec, 2005]. This paper is concerned with the multi-objectives resource allocation problem. Our objective is to find adequate resource allocation for given courses of action schedule. To optimize this problem, this paper investigates non-exact solution methods, like meta-heuristic methods for finding potential efficient solutions. A progressive resource allocation methodology is proposed based on Tabu Search and multi-objectives concepts. This technique explores the search space so as to find a set of potential efficient solutions without aggregating the objectives into a single objective function. It is guided by the principle of maximizing the usage of any resource before considering a replacement resource. Thus, a given resource is allocated to the maximum number of tasks for a given courses of action schedule. A good allocation is a potential efficient solution. These solutions are retained by applying a combination of a dominance rule and a multi-criteria filtering method. The performance of the proposed Pareto-based approach is compared to two aggregation approaches: weighted-sum and the lexicographic techniques. The result shows that a Pareto-based approach is providing better solutions and allowing more flexibility to the decision-maker.