Decision Support System For Allocation Research Articles

A Multi-Attribute Decision Support System for Allocation of Humanitarian Cluster Resources Based on Decision Makers’ Perspective

The rush of the humanitarian suppliers into the disaster area proved to be counter-productive. To reduce this proliferation problem, the present research is designed to provide a technique for supplier ranking/selection in disaster response using the principles of utility theory. A resource allocation problem is solved using optimisation based on decision maker’s preferences. Due to the lack of real-time data in the first 72 h after the disaster strike, a Decision Support System (DSS) framework called EDIS is introduced to employ secondary historical data from disaster response in four humanitarian clusters (WASH: Water, Sanitation and Hygiene, Nutrition, Health, and Shelter) to estimate the demand of the affected population. A methodology based on multi-attribute decision-making (MADM), Analytical Hierarchy processing (AHP) and Multi-attribute utility theory (MAUT) provides the following results. First a need estimation technique is put forward to estimate minimum standard requirements for disaster response. Second, a method for optimization of the humanitarian partners selection is provided based on the resources they have available during the response phase. Third, an estimate of resource allocation is provided based on the preferences of the decision makers. This method does not require real-time data from the aftermath of the disasters and provides the need estimation, partner selection and resource allocation based on historical data before the MIRA report is released.

Decision support system of nursing human resources allocation in general wards based on hospital information system

Objective To construct a decision support system of nursing human resources allocation in general wards. Methods Based on data of hospital information system in one tertiary hospital, data warehouse, model database and human computer interaction were constructed by some information technology. Results This study completed the function design and system implementation of the nursing human resources allocation decision support system. Conclusions The system would help nursing managers choose the optimal nursing manpower allocation scheme and make scientific decisions in combination with actual nursing workload. Key words: Hospital information system; Decision support system, management; Nursing staff, hospital; Hospital administration

Establishing an order allocation decision support system via learning curve model for apparel logistics

Apparel firms confront the problem with effective order allocation among factories when conducting global logistics operations. The problem is non-deterministic polynomial-time hard and often complicated to obtain an optimal solution. This research tried to solve, by heuristic method, the problem via applying the learning curve to the capacity planning to improve the decision-making on global logistics operations. It designed a two-stage order allocation decision support system. This two-stage model includes: (1) selecting and sorting factories and (2) dynamic learning of order allocation. The results demonstrated that the system could develop the most suitable order allocation model among multiple factories and minimize the order allocation cost. This research further provided a case study to help verify the designed system applied in the global logistics operations of apparel industry. The proposed system seems to be more conforming to the real-world production and could offer a better suggestion concerning order allocation.

A Decision Support System for Allocation of Mountain Forest Roads Based on Ground Stability

The main purpose of this research was to introduce a method for planning forest road network by combining geographical information system (GIS) and analytic hierarchy process (AHP) in a form that environmental factors such as ground stability were incorporated in the planning process. After collection of data and building the necessary maps of study area, the effective factors in forest road allocation were identified and forest potential to road construction was determined and classified. After that, the maps of slope, volume per hectare, aspect, altitude, forest type, and ground stability were prepared. In the next step, concerning the importance and the role of the mentioned elements in the road construction cost, prepared maps were rated using AHP to determine the weight of both the effective factors and their categories. Then, forest potential map of road construction was prepared by overlaying the weighted maps of the mentioned factors. The later map was categorized to three classes including high, moderate and low capability. The results of this study showed that about 88% of the proposed roads were located in the regions with high and moderate road construction capability; as well, it provided an accessibility of 80% for the plan area. Results also showed that using of a GIS–AHP method could improve the accessibility to the district and could ensure that routs will pass from stable regions. The introduced method can be used as a useful method for planning of forest road network in mountain areas.

River Temperature Forecasting: A Coupled-Modeling Framework for Management of River Habitat

Humans have substantially altered the thermal regimes of freshwater habitats worldwide, with significant environmental consequences. There is a critical need for a comprehensive modeling framework for forecasting the downstream impacts of two of the most common anthropogenic structures that alter river water temperatures: 1) dams that selectively release water from thermally stratified reservoirs, and 2) power generating stations and industrial plants that use river water for once-through cooling. These facilities change the thermal dynamics of the downstream waters through a complex interaction of water release volume and temperature and the subsequent exchange with the environment downstream. In order to stay within the downstream temperature limits imposed by regulatory agencies, managers must monitor not just release volumes and temperatures, but also need to be able to forecast the thermal impacts of their day-to-day operations on habitat which may be hundreds of kilometers downstream. Here we describe a coupled modeling framework that links mesoscale weather and ecological models to generate inputs for a physically-based water temperature model for monitoring and forecasting river temperatures downstream from these facilities at fine spatiotemporal scales. We provide an example of how this modeling framework is being applied to a water allocation decision support system (DSS) for the management of Endangered Species Act (ESA) listed salmon species in the Sacramento River in California.

Multi-strategy budget allocation decision support system for seismic rehabilitation of road infrastructure

Economic efficiency is an important factor in seismic rehabilitation of road infrastructures. An inventory of structures is screened to identify seismically deficient parts and prioritise them in the order of need for rehabilitation purposes. In most cases, the financial resources for road infrastructure rehabilitation projects are limited. Therefore, there is a need to efficiently allocate resources to various projects. This article presents a multi-strategy decision support system (DSS) for seismic rehabilitation budget allocation across existing road infrastructures. This DSS employs a multi-criteria assessment module that takes into account different criteria to estimate the financial needs for rehabilitation and to establish an allocation methodology based on the available budget in a fiscal year. To select the optimal package of projects, a genetic algorithm (GA) optimisation module is developed. Multi-objective decision-making is conducted under a specific decision strategy (DS) by solving a (0–1) Knapsack problem. To demonstrate the applicability of the GA-based approach, a hypothetical decision-making problem is presented. The results reveal that the optimal package is more sensitive to the available budget and DS than to the weights of criteria and project scores. Using this system, managers can compare their decisions for different strategies and significantly improve management efficiency.

IT—Information Technology: An Individual Feed Allocation Decision Support System for the Dairy Farm

A decision-support system that allocates concentrated feed to cows through individual feeders according to their performance has been developed using fuzzy logic. Fuzzy sets were constructed by analysing experimental data based on which ranges of values for the fuzzy sets members were determined by an expert. The model was developed on a group of 15 cows in a dairy of 50 milking cows (two milkings a day) under a controlled dietary regime, assuming characteristic cow behaviour concerning body weight, milk yield, lactation period, and concentrate feed consumption. The data were analysed by the decision-support system and compared to weekly decisions of the expert. Results indicated relationship between historical cow performances and concentrated food intake. The advantage of using fuzzy logic was that it enabled improved concentrate feeding ration according to performance. The system enabled to automate decision making, thus providing the farmer with a valuable tool. However, from an economic point of view no significant statistical improvement was achieved by the fuzzy logic system.

Assigning Students to Groups: A Multi‐Criteria Decision Support System Approach*

ABSTRACTMCADSS is a multi‐criteria allocation decision support system for assisting in the task of allocating students to groups. Based on multiple criteria, MCADSS's goal is to maximize the diversity of members within groups, while minimizing the average differences between groups. The project may be viewed from several perspectives: as a multi‐criteria decision‐making problem, as a “reverse'’clustering problem, or as a personnel assignment problem. The system is currently being used to allocate M.B.A. students into sections and study teams at The European Institute of Business Administration (INSEAD). This paper describes the rationale for MCADSS, design criteria, system methodology, and application results. It also suggests how this approach could be used for further applications.

A decision support system for capital budgeting and allocation

Abstract This paper presents a capital budgeting and allocation decision support system (CBA-DSS) for big organizations that have many planning units (branch offices and/or departments). This CBA-DSS is designed to be generalized so that it can be used by many organizations in the real world. Two types of budgets, project type and flexible type , are considered to cater to different types of categories. Three modeling techniques are used in the development of this DSS: zero-one integer linear programming is used to get the optimal solutions; forecasting techniques provide the predicted values through historical data; and fuzzy sets approach is used to assign weighting factors to selected criteria in determining the flexible type budget. Two useful capabilities are included: “ HELP ” screens and demonstration programs. The users can understand the basic operations of CBA-DSS through demonstration programs and “ HELP ” screens without reading a bulky manual. CBA-DSS, which is designed to be highly user-friendly, menu-driven and interactive, will help the managers (of medium as well as top level) in their decision making process of planning and allocating limited budget to their planning units effectively and efficiently.

A microcomputer-based decision support system for scholarship allocation

A decision support system for the allocation of scholarships at the Asian Institute of Technology (AIT) has been designed and implemented on an MS-DOS microcomputer employing micro-PROLOG language. The system is driven by a menu each module of which relates to a single major stage in the allocation process. It integrates many facilities ranging from routine data manipulation to functions demanding a certain degree of human intelligence. It is able to produce report-formatted display, coloured bar graphs and other visual aids on the screen. Its allocation module will answer questions relating to the system's procedures and reasoning when a certain student has been given a grant from a certain donor. The system has been run using actual AIT scholarship data for the year 1983–1984, and its output has been compared with the manual allocation of the Institute's donor officer. It produced a fair scholarship distribution and was able to simplify the officer's task by enabling her to try out with little effort different grant combinations.