Techniques for the allocation of resources under uncertainty

L’allocation de ressources est un problème omniprésent qui survient dès que des ressources limitées doivent être distribuées parmi de multiples agents autonomes (e.g., personnes, compagnies, robots, etc). Les approches standard pour déterminer l’allocation optimale souffrent généralement d’une très grande complexité de calcul. Le but de cette thèse est de proposer des algorithmes rapides et efficaces pour allouer des ressources consommables et non consommables à des agents autonomes dont les préférences sur ces ressources sont induites par un processus stochastique. Afin d’y parvenir, nous avons développé de nouveaux modèles pour des problèmes de planifications, basés sur le cadre des Processus Décisionnels de Markov (MDPs), où l’espace d’actions possibles est explicitement paramétrisés par les ressources disponibles. Muni de ce cadre, nous avons développé des algorithmes basés sur la programmation dynamique et la recherche heuristique en temps-réel afin de générer des allocations de ressources pour des agents qui agissent dans un environnement stochastique. En particulier, nous avons utilisé la propriété acyclique des créations de tâches pour décomposer le problème d’allocation de ressources. Nous avons aussi proposé une stratégie de décomposition approximative, où les agents considèrent des interactions positives et négatives ainsi que les actions simultanées entre les agents gérants les ressources. Cependant, la majeure contribution de cette thèse est l’adoption de la recherche heuristique en temps-réel pour l’allocation de ressources. À cet effet, nous avons développé une approche basée sur la Q-décomposition munie de bornes strictes afin de diminuer drastiquement le temps de planification pour formuler une politique optimale. Ces bornes strictes nous ont permis d’élaguer l’espace d’actions pour les agents. Nous montrons analytiquement et empiriquement que les approches proposées mènent à des diminutions de la complexité de calcul par rapport à des approches de planification standard. Finalement, nous avons testé la recherche heuristique en temps-réel dans le simulateur SADM, un simulateur d’allocation de ressource pour une frégate.Resource allocation is an ubiquitous problem that arises whenever limited resources have to be distributed among multiple autonomous entities (e.g., people, companies, robots, etc). The standard approaches to determine the optimal resource allocation are computationally prohibitive. The goal of this thesis is to propose computationally efficient algorithms for allocating consumable and non-consumable resources among autonomous agents whose preferences for these resources are induced by a stochastic process. Towards this end, we have developed new models of planning problems, based on the framework of Markov Decision Processes (MDPs), where the action sets are explicitly parameterized by the available resources. Given these models, we have designed algorithms based on dynamic programming and real-time heuristic search to formulating thus allocations of resources for agents evolving in stochastic environments. In particular, we have used the acyclic property of task creation to decompose the problem of resource allocation. We have also proposed an approximative decomposition strategy, where the agents consider positive and negative interactions as well as simultaneous actions among the agents managing the resources. However, the main contribution of this thesis is the adoption of stochastic real-time heuristic search for a resource allocation. To this end, we have developed an approach based on distributed Q-values with tight bounds to diminish drastically the planning time to formulate the optimal policy. These tight bounds enable to prune the action space for the agents. We show analytically and empirically that our proposed approaches lead to drastic (in many cases, exponential) improvements in computational efficiency over standard planning methods. Finally, we have tested real-time heuristic search in the SADM simulator, a simulator for the resource allocation of a platform

Target threat assessment using fuzzy sets theory

The threat evaluation is significant component in target classification process and is significant in military and non military applications. Small errors or mistakes in threat evaluation and target classification especial in military applications can result in huge damage of life and property. Threat evaluation helps in case of weapon assignment, and intelligence sensor support system. It is very important factor to analyze the behavior of enemy tactics as well as our surveillance. This paper represented a precise description of the threat evaluation process using fuzzy sets theory. A review has been carried out regarding which parameters that have been suggested for threat value calculation. For the first time in this paper, eleven parameters are introduced for threat evaluation so that this parameters increase the accuracy in designed system. The implemented threat evaluation system has been applied to a synthetic air defense scenario and four real time dynamic air defense scenarios. The simulation results show the correctness, accuracy, reliability and minimum errors in designing of threat evaluation syste

A Survey on Weapon Target Allocation Models and Applications

In Command and Control (C2), Threat Evaluation (TE) and Weapon Target Allocation (WTA) are two key components. To build an automated system in this area after modeling Threat Evaluation and Weapon Target Allocation processes, solving these models and finding the optimal solution are further important issues. This setting demands instantaneous operational planning and decision making under inherent severe stress conditions. The associated responsibilities are usually divided among a number of operators and also computerized decision support systems that aid these operators during the decision making process. In this Chapter, the literature in the area of WTA system with the emphasis on the modeling and solving methods are surveyed

Operations Research in the High Tech Military Environment: A Survey

The use of operations research as a technology to solve many of the problems of government and industry has become a major field of study within the very short span of the last fifty years. In the paper entitled, Operations Research in the High Tech Military Environment: A Survey, the reader is provided with a better understanding of the tenets of operations research through an examination of a representative sample of the latest operations research applications developed for the high tech environment. Initially, this involves providing the reader with some fundamental insights into what operations research is, what its practitioners do, and how the state-of-the-art has evolved to its present form. It then involves providing a brief description of what is meant by the term, high tech military environment. A survey, which constitutes the bulk of the material presented, focuses on how various operations research methodologies are being used within that environment. The paper concludes with a discussion of the possible directions operations research will take in the future, based on the present state-of-the-art

Development and demonstration of a performance evaluation framework for threat evaluation and weapon assignment systems

Thesis (MEng)--Stellenbosch University, 2016.ENGLISH ABSTRACT: defending ground assets against aerial threats. These weapon systems are employed in conjunction with an array of sensor systems which are capable of detecting and tracking aerial threats, and providing information for determining the level of danger that the threats pose to the defended system. In this context, the purpose of a Threat Evaluation and Weapon Assignment (TEWA) system is to provide decision support to the human operators who are tasked with assigning weapon systems to counter the aerial threats. The TEWA system typically assigns appropriate system threat values to each of the aerial threats which indicates the level of danger they pose to the defended system. These system threat values are used, in turn, when seeking to optimise the allocation of weapon systems to threats in such a way that the weighted cumulative survival probability of the aerial threats is minimised. These weapon allocations are suggested to a human operator for implementation via a human machine interface. A large number of TEWA systems are already in use around the world, but due to the confidential nature of this research area, descriptions of the working of these systems are typically not available in the open literature. Despite the critical role these systems play in the current, evolving network-centric warfare environment, there exists no generic framework in the literature for evaluating the performance of TEWA systems. The work contained in this thesis therefore adds to the South African TEWA knowledge base by determining the extent to which current TEWA-related research in a ground-based air-defense environment forms a coherent foundation from which further system development and performance evaluation can continue. This broad research aim is achieved by developing a performance evaluation simulation framework for TEWA systems and demonstrating the feasibility of locally developed TEWA algorithms. A system-of-systems simulation modelling approach is adopted in the design of this framework. Using the framework, limitations present in the TEWA algorithms are identified and mitigation strategies are suggested. These strategies include a novel threat value fusion methodology, an alternative weapon system modelling approach and the implementation of a genetic algorithm for solving the weapon allocation problem approximately. Design requirements for an effective human machine interface are also described in some detail and several TEWA system performance metrics are suggested. The working of the framework is finally demonstrated in the context of a comprehensive, near-realistic, but hypothetical, ground-based air-defense scenario.AFRIKAANSE OPSOMMING: In 'n militêre lugafweeromgewing word grond-gebaseerde wapenstelsels gebruik om grondbates teen lugbedreigings te beskerm. Hierdie wapenstelsels word in oorleg met 'n aantal sensorstelsels aangewend wat daartoe in staat is om lugbedreigings op te spoor en te volg, en inligting te verskaf waarvolgens die vlak van gevaar wat hierdie bedreigings vir die verdedigde stelsel inhou, bepaal kan word. In hierdie konteks is die doel van 'n Bedreigingsafskatting-en-wapentoewysing (TEWA) stelsel om besluitsteun aan menslike operateurs te bied wat daarvoor verantwoordelik is om wapenstelsels aan lugbedreigings toe te ken. Die TEWA stelsel heg tipies 'n gepaste stelsel-wye bedreigingswaarde aan elkeen van die lugbedreigings wat die vlak van gevaar aandui wat hul met betrekking tot die verdedigde stelsel inhou. Hierdie stelsel-wye bedreigingswaardes word dan gebruik in die soeke na optimale toewysings van wapenstelsels aan die bedreigings om sodoende die geweegde, geakkumuleerde oorlewingswaarskynlikheid van die lugbedreigings te minimeer. Wapentoewysingsvoorstelle word deur middel van 'n mens-masjien koppelvlak aan 'n menslike operateur vir implementasie voorgel^e. 'n Groot getal TEWA stelsels is reeds w^ereldwyd in gebruik, maar as gevolg van die vertroulike aard van hierdie navorsingsgebied, is beskrywings van die werking van hierdie stelsels tipies nie in die oop literatuur beskikbaar nie. Ten spyte van die kritiese rol wat hierdie stelsels in die huidige, evoluerende netwerk-sentriese oorlogvoeringsomgewing speel, bestaan daar geen generiese raamwerke in die literatuur waarvolgens die werkverrigting van TEWA stelsels geëvalueer kan word nie. Die werk wat in hierdie tesis vervat is, dra dus by tot die Suid-Afrikaanse TEWA stelselkennisbasis deur vas te stel tot watter mate die huidige TEWA stelsel-verwante navorsing in die konteks van 'n grond-gebaseerde lugafweeromgewing 'n samehorige grondslag vorm waarop verdere stelselontwikkeling en werkverrigtingsanalise kan voortbou. Hierdie breë navorsingsdoel word bereik deur 'n simulasieraamwerk daar te stel waarvolgens die werkverrigting van TEWA stelsels gemeet kan word en met behulp waarvan die werkbaarheid van plaaslik-ontwikkelde TEWA algoritmes gedemonstreer kan word. Deur van die raamwerk gebruik te maak, word beperkings in die TEWA algoritmes geïdentifiseer en word strategieë voorgestel waarvolgens hierdie beperkings reggestel kan word. Hierdie strategieë sluit in 'n nuwe metodologie vir die samevoeging van bedreigingswaardes, 'n alternatiewe wapenstelsel-modelleringsbenadering en die implementasie van 'n genetiese algoritme vir die benaderde oplossing van die wapentoewysingsprobleem. Ontwerpsvereistes vir 'n doeltreffende mens-masjien koppelvlak word ook noukeurig beskryf, en 'n aantal TEWA stelsel werkverrigtingsmaatstawwe word voorgestel. Die werking van die raamwerk word uiteindelik aan die hand van 'n omvattende, byna realistiese, maar hipotetiese, grond-gebaseerde lugafweerscenario gedemonstreer

Considerations for Cross Domain / Mission Resource Allocation and Replanning

NPS NRP Technical ReportNaval platforms are inherently multi-mission - they execute a variety of missions simultaneously. Ships, submarines, and aircraft support multiple missions across domains, such as integrated air and missile defense, ballistic missile defense, anti-submarine warfare, strike operations, naval fires in support of ground operations, and intelligence, surveillance, and reconnaissance. Scheduling and position of these multi-mission platforms is problematic since one warfare area commander desires one position and schedule, while another may have a completely different approach. Commanders struggle to decide and adjudicate these conflicts, because there is plenty of uncertainty about the enemy and the environment. This project will explore emerging innovative data analytic technologies to optimize naval resource allocation and replanning across mission domains. NPS proposes a study that will evaluate the following three solution concepts for this application: (1) game theory, (2) machine learning, and (3) wargaming. The study will first identify a set of operational scenarios that involve distributed and diverse naval platforms and resources and a threat situation that requires multiple concurrent missions in multiple domains. The NPS team will use these scenarios to evaluate the three solution concepts and their applicability to supporting resource allocation and replanning. This project will provide valuable insights into innovative data analytic solution concepts to tackle the Navy's challenge of conducing multiple missions with cross-domain resources.N2/N6 - Information WarfareThis research is supported by funding from the Naval Postgraduate School, Naval Research Program (PE 0605853N/2098). https://nps.edu/nrpChief of Naval Operations (CNO)Approved for public release. Distribution is unlimited.

Improvement of Work Process Performance with Task Assignments and Mental Workload Balancing

The outcome of a work process depends heavily on which tasks assigned to which employees. However, sometimes-optimized assignments based on employees’ qualifications may result in an uneven and ineffective workload distribution among them. Likewise, an even workload distribution without considering the employee\u27s qualifications may cause unproductive employee-task matching that results in low performance of employees. This trade-off is even more noticeable for work processes during critical time junctions, such as in military command centers and emergency rooms that require being fast and effective without making errors. This study proposes that optimizing task-employee assignments according to their capabilities while also keeping them under a workload threshold, results in better performance for work processes, especially during critical time junctions. The goal is to select the employee-task assignments in order to minimize the average duration of a work process while keeping the employees under a workload threshold to prevent errors caused by overload. Due to uncertainties inherent in the problem related with the inter-arrival time of work orders, task durations and employees\u27 instantaneous workload, a utilized simulation-optimization approach solves this problem. More specifically, a discrete event human performance simulation model evaluates the objective function of the problem coupled with a genetic algorithm based meta-heuristic optimization approach to search the solution space. This approach proved to be useful in determining the right task-agent assignments by taking into consideration the employees\u27 qualifications and mental workload in order to minimize the average duration of a work process. Use of a sample work process shows the effectiveness of the developed simulation-optimization approach. Numerical tests indicate that the proposed approach finds better solutions than common practices and other simulation-optimization methods. Accordingly, by using this method, organizations can increase performance, manage excess-level workloads, and generate higher satisfactory environments for employees, without modifying the structure of the process itself

Multi-platform coordination and resource management in command and control

Depuis plusieurs années, nous constatons l'augmentation de l'utilisation des techniques d'agents et multiagent pour assister l'humain dans ses tâches. Ce travail de maîtrise se situe dans la même voie. Précisément, nous proposons d'utiliser les techniques multiagent de planification et de coordination pour la gestion de ressources dans les systèmes de commande et contrôle (C2) temps réel. Le problème particulier que nous avons étudié est la conception d'un système d'aide à la décision pour les opérations anti-aérienne sur les frégates canadiennes. Dans le cas où plusieurs frégates doivent se défendre contre des menaces, la coordination est un problème d'importance capitale. L'utilisation de mécanismes de coordination efficaces permet d'éviter les actions conflictuelles et la redondance dans les engagements. Dans ce mémoire, nous présentons quatre mécanismes de coordination basés sur le partage de tâche. Trois sont basés sur les communications : la coordination centrale, le Contract Net, la coordination similaire à celle proposée par Brown; tandis que la défense de zone est basée sur les lois sociales. Nous exposons enfin les résultats auxquels nous sommes arrivés en simulant ces différents mécanismes.The use of agent and multiagent techniques to assist humans in their daily routines has been increasing for many years, notably in Command and Control (C2) systems. This thesis is is situated in this domain. Precisely, we propose to use multiagent planning and coordination techniques for resource management in real-time \acs{C2} systems. The particular problem we studied is the design of a decision-support for anti-air warfare on Canadian frigates. In the case of several frigates defending against incoming threats, multiagent coordination is a complex problem of capital importance. Better coordination mechanisms are important to avoid redundancy in engagements and inefficient defence caused by conflicting actions. In this thesis, we present four different coordination mechanisms based on task sharing. Three of these mechanisms are based on communications: central coordination, Contract Net coordination and Brown coordination, while the zone defence coordination is based on social laws. Finally, we expose the results obtained while simulating these various mechanisms