  In today's dynamic and interconnected world, resource constraints pose
significant challenges across various domains, ranging from networks, logistics
and manufacturing to project management and optimization, etc.
Resource-constrained problems (RCPs) represent a class of complex computational
problems that require efficient allocation and utilization of limited resources
to achieve optimal outcomes. This thesis aims to delve into such problems
involving multiple agents, where agents aim to enhance their own payoffs, or a
neutral moderator aims to maximise the system revenue while distributing the
resources appropriately among all agents. In the former type of problems,
agents may seek collaboration to achieve higher individual shares, resulting in
a cooperative game with competition, i.e., co-opetition. Cooperative and
non-cooperative game theory tools are utilized to analyze such games. On the
other hand, for the latter kind of problems, we use tools from optimization and
Markov decision processes.
