scholarly journals Efficient Strategies Algorithms for Resource Allocation Problems

Algorithms ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 270
Author(s):  
Yacouba Adama Koné ◽  
Jacqueline Konaté ◽  
Oumar Y. Maïga ◽  
Hamidou Tembiné
Keyword(s):  
Decision Making ◽  
Resource Allocation ◽  
Incomplete Information ◽  
Case Studies ◽  
Complexity Analysis ◽  
Strategic Learning ◽  
Panoramic View ◽  
Colonel Blotto ◽  
New Strategies ◽  
Allocation Strategies

Strategic modelling with a panoramic view plays an important role in decision-making problems. It offers the possibility of generating different solutions before making a decision. This is particularly relevant in critical situations. This article addresses the problem of allocating resources, whether financial, material or human, so that it is optimal under a given set of constraints and inter-dependencies with other systems. To do this, existing strategies such as those of Colonel Blotto are studied in order to evaluate them according to some criteria, including the heterogeneity or homogeneity of resources and/or battlefields. Based on the results of these configurations, we propose distributed strategic learning methods to find better resource allocation strategies. The proposed algorithms are implemented under various scenarios, including incomplete information. Case studies are carried out to test the effectiveness of these new strategies compared to previous ones. A complexity analysis of the different algorithms is also presented.

CASE STUDIES THAT ILLUSTRATE DISINVESTMENT AND RESOURCE ALLOCATION DECISION-MAKING PROCESSES IN HEALTH CARE: A SYSTEMATIC REVIEW

2013 ◽  
Vol 29 (2) ◽  
pp. 174-184 ◽  
Author(s):  
Julie Polisena ◽  
Tammy Clifford ◽  
Adam G. Elshaug ◽  
Craig Mitton ◽  
Erin Russell ◽  
...  
Keyword(s):  
Health Care ◽  
Decision Making ◽  
Resource Allocation ◽  
Case Studies ◽  
Resource Allocation Decision ◽  
Cochrane Library ◽  
Fee For Service ◽  
Allocation Decision ◽  
Allocation Decisions ◽  
Resource Allocation Decisions

Objective:Technological change accounts for approximately 25 percent of health expenditure growth. To date, limited research has been published on case studies of disinvestment and resource allocation decision making in clinical practice. Our research objective is to systematically review and catalogue the application of frameworks and tools for disinvestment and resource allocation decision making in health care.Methods:An electronic literature search was executed for studies on disinvestment, obsolete and ineffective technologies, and priority healthcare setting, published from January 1990 until January 2012. Databases searched were MEDLINE, MEDLINE In-Process and Other Non-Indexed Citations, Embase, The Cochrane Library, PubMed, and HEED.Results:Fourteen case studies on the application of frameworks and tools for disinvestment and resource allocation decisions were included. Most studies described the application of program budgeting and marginal analysis (PBMA), and two reports used health technology assessment (HTA) methods for coverage decisions in a national fee-for-service structure. Numerous healthcare technologies and services were covered across the studies. We describe the multiple criteria considered for decision making, and the strengths and limitations of these frameworks and tools are highlighted.Conclusions:Disinvestment and resource allocation decisions require evidence to ensure their transparency and objectivity. PBMA was used to assess resource allocation of health services and technologies in a fixed budget jurisdiction, while HTA reviews focused on specific technologies, principally in fee-for-service structures. Future research can review the data requirements and explore opportunities to increase the quantity of available evidence for disinvestment and resource allocation decisions.

Megadrought and Collapse

2017 ◽  
Keyword(s):  
Climate Change ◽  
Decision Making ◽  
Case Studies ◽  
Agricultural Landscapes ◽  
15Th Century ◽  
Societal Collapse ◽  
The Face ◽  
Time Periods ◽  
Paleoclimate Proxy ◽  
Habitat Tracking

This is the first book to treat the major examples of megadrought and societal collapse, from the late Pleistocene end of hunter–gatherer culture and origins of cultivation to the 15th century AD fall of the Khmer Empire capital at Angkor, and ranging from the Near East to South America. Previous enquiries have stressed the possible multiple and internal causes of collapse, such overpopulation, overexploitation of resources, warfare, and poor leadership and decision-making. In contrast, Megadrought and Collapse presents case studies of nine major episodes of societal collapse in which megadrought was the major and independent cause of societal collapse. In each case the most recent paleoclimatic evidence for megadroughts, multiple decades to multiple centuries in duration, is presented alongside the archaeological records for synchronous societal collapse. The megadrought data are derived from paleoclimate proxy sources (lake, marine, and glacial cores; speleothems, or cave stalagmites; and tree-rings) and are explained by researchers directly engaged in their analysis. Researchers directly responsible for them discuss the relevant current archaeological records. Two arguments are developed through these case studies. The first is that societal collapse in different time periods and regions and at levels of social complexity ranging from simple foragers to complex empires would not have occurred without megadrought. The second is that similar responses to megadrought extend across these historical episodes: societal collapse in the face of insurmountable climate change, abandonment of settlements and regions, and habitat tracking to sustainable agricultural landscapes. As we confront megadrought today, and in the likely future, Megadrought and Collapse brings together the latest contributions to our understanding of past societal responses to the crisis on an equally global and diverse scale.

Game-Based Resource Allocation Mechanism in B5G HetNets with Incomplete Information

2020 ◽  
Vol 10 (5) ◽  
pp. 1557
Author(s):  
Weijia Feng ◽  
Xiaohui Li
Keyword(s):  
Resource Allocation ◽  
Incomplete Information ◽  
Stackelberg Game ◽  
Superior Performance ◽  
Channel Gain ◽  
Mobile Users ◽  
Pricing Strategies ◽  
Game Equilibrium ◽  
Allocation Process ◽  
Realistic Situation

Ultra-dense and highly heterogeneous network (HetNet) deployments make the allocation of limited wireless resources among ubiquitous Internet of Things (IoT) devices an unprecedented challenge in 5G and beyond (B5G) networks. The interactions among mobile users and HetNets remain to be analyzed, where mobile users choose optimal networks to access and the HetNets adopt proper methods for allocating their own network resource. Existing works always need complete information among mobile users and HetNets. However, it is not practical in a realistic situation where important individual information is protected and will not be public to others. This paper proposes a distributed pricing and resource allocation scheme based on a Stackelberg game with incomplete information. The proposed model proves to be more practical by solving the problem that important information of either mobile users or HetNets is difficult to acquire during the resource allocation process. Considering the unknowability of channel gain information, the follower game among users is modeled as an incomplete information game, and channel gain is regarded as the type of each player. Given the pricing strategies of networks, users will adjust their bandwidth requesting strategies to maximize their expected utility. While based on the sub-equilibrium obtained in the follower game, networks will correspondingly update their pricing strategies to be optimal. The existence and uniqueness of Bayesian Nash equilibrium is proved. A probabilistic prediction method realizes the feasibility of the incomplete information game, and a reverse deduction method is utilized to obtain the game equilibrium. Simulation results show the superior performance of the proposed method.

scholarly journals Assessing the Value of Demand Response in Microgrids

2021 ◽  
Vol 13 (11) ◽  
pp. 5848
Author(s):  
Isaías Gomes ◽  
Rui Melicio ◽  
Victor M. F. Mendes
Keyword(s):  
Decision Making ◽  
Energy Consumption ◽  
Energy Storage ◽  
Case Studies ◽  
Demand Response ◽  
Storage Systems ◽  
Computer Application ◽  
Market Prices ◽  
Proper Formulation ◽  
Operation Case

This paper presents a computer application to assist in decisions about sustainability enhancement due to the effect of shifting demand from less favorable periods to periods that are more convenient for the operation of a microgrid. Specifically, assessing how the decisions affect the economic participation of the aggregating agent of the microgrid bidding in an electricity day-ahead market. The aggregating agent must manage microturbines, wind systems, photovoltaic systems, energy storage systems, and loads, facing load uncertainty and further uncertainties due to the use of renewable sources of energy and participation in the day-ahead market. These uncertainties cannot be removed from the decision making, and, therefore, require proper formulation, and the proposed approach customizes a stochastic programming problem for this operation. Case studies show that under these uncertainties and the shifting of demand to convenient periods, there are opportunities to make decisions that lead to significant enhancements of the expected profit. These enhancements are due to better bidding in the day-ahead market and shifting energy consumption in periods of favorable market prices for exporting energy. Through the case studies it is concluded that the proposed approach is useful for the operation of a microgrid.

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