Agent-based computing has attracted much attention as a promising technique for application domains that are distributed, complex and heterogeneous. Current research on multi-agent systems (MAS) has become mature enough to be applied as a technology for solving problems in an increasingly wide range of complex applications. The main formal architectures used to describe the relationships between agents in MAS are centralised and distributed architectures. In computational complexity theory, researchers have classified the problems into the followings categories: (i) P problems, (ii) NP problems, (iii) NP-complete problems, and (iv) NP-hard problems. A method for computing the solution to NP-hard problems, using the algorithms and computational power available nowadays in reasonable time frame remains undiscovered. And unfortunately, many practical problems belong to this very class. On the other hand, it is essential that these problems are solved, and the only possibility of doing this is to use approximation techniques. Heuristic solution techniques are an alternative. A heuristic is a strategy that is powerful in general, but not absolutely guaranteed to provide the best (i.e. optimal) solutions or even find a solution. This demands adopting some optimisation techniques such as Evolutionary Algorithms (EA). This research has been undertaken to investigate the feasibility of running computationally intensive algorithms on multi-agent architectures while preserving the ability of small agents to run on small devices, including mobile devices. To achieve this, the present work proposes a new Hybrid Multi-Agent Architecture (HMAA) that generates new heuristics for solving NP-hard problems. This architecture is hybrid because it is "semi-distributed/semi-centralised" architecture where variables and constraints are distributed among small agents exactly as in distributed architectures, but when the small agents become stuck, a centralised control becomes active where the variables are transferred to a super agent, that has a central view of the whole system, and possesses much more computational power and intensive algorithms to generate new heuristics for the small agents, which find optimal solution for the specified problem. This research comes up with the followings: (1) Hybrid Multi-Agent Architecture (HMAA) that generates new heuristic for solving many NP-hard problems. (2) Two frameworks of HMAA have been implemented; search and optimisation frameworks. (3) New SMA meeting scheduling heuristic. (4) New SMA repair strategy for the scheduling process. (5) Small Agent (SMA) that is responsible for meeting scheduling has been developed. (6) “Local Search Programming” (LSP), a new concept for evolutionary approaches, has been introduced. (7) Two types of super-agent (LGP_SUA and LSP_SUA) have been implemented in the HMAA, and two SUAs (local and global optima) have been implemented for each type. (8) A prototype for HMAA has been implemented: this prototype employs the proposed meeting scheduling heuristic with the repair strategy on SMAs, and the four extensive algorithms on SUAs. The results reveal that this architecture is applicable to many different application domains because of its simplicity and efficiency. Its performance was better than many existing meeting scheduling architectures. HMAA can be modified and altered to other types of evolutionary approaches.

Практическая значимость данной выпускной квалификационной работы связана с изложенной в ней разработкой системы централизованного управления трансляцией контента, которая успешно реализуется на рынке. С внедрением информационных технологий в нашу жизнь изменяется характер предоставления публичной информации в обществе. На смену бумажным вариантам объявлений и вывесок приходят электронные аналоги, отличающиеся высокой яркостью, динамичность, скоростью обновления информации. Высокий спрос на оперативное, централизованное обновление транслируемого на экраны контента, способствовал появлению на рынке “цифровых вывесок” систем Digital Signage, позволяющих централизованно управлять показываемым контентом на распределенной сети медиа устройств, обновлять его, не производя манипуляций непосредственно с каждым девайсом. Результатом работы является разработанная система управления контентом MMVS Digital Signage, которая успешно реализуется на рынке и дает компании ряд конкурентных преимуществ. Результаты работы подтверждены расчетами экономических показателей. / The practical significance of this final qualifying work is associated with the development of a system for centralized content broadcasting management, which is successfully implemented on the market, as described in it. With the introduction of information technology into our life, the nature of the provision of public information in society is changing. The paper versions of advertisements and signs are being replaced by electronic counterparts, which are distinguished by high brightness, dynamism, and the speed of information updating. The high demand for prompt, centralized updating of content broadcasted to screens has contributed to the appearance on the market of “digital signage” of Digital Signage systems, which allow centrally managing the displayed content on a distributed network of media devices, updating it without manipulating directly with each device. The result of the work is the developed content management system MMVS Digital Signage, which is successfully implemented in the market and gives the company a number of competitive advantages. The results of the work are confirmed by calculations of economic indicators.