Dynamism is known as an attempt to explain the phenomena of the universe against some immediate change. All scientists dealing with the systems and phenomena of the universe have unsurprisingly been faced with a variety of immediate change. Therefore, they are usually obligated to ignore more than one variable to keep change at a time. However, with the storm of technological change, it has been difficult to deal with the increasing dynamism and the uncertainty with the existing manner. Providentially, new computing and programming utilities like agent technology have enabled more realistic modeling. In this respect, a typical operations research problem including constraints, objective functions and variables could have been altered with the more realistic ones where constraints, objective functions and domains of variables can be a matter of any kind of change at any time. To cope with such dynamism, there have been several efforts to adapt some of the meta-heuristics to work in a harmony and in integrity without ignoring the objective(s) of modeling. This usually requires agent-based approaches letting the elements (such as ants, bees or gens) to communicate and negotiate with each other in order to adapt themselves in parallel to the changes in the domain of variables, constraints and objective functions. Although meta-heuristic approaches for the solution of dynamic optimization problems are relatively new in the literature, this paper intends to review and analyze existing studies that are available in the literature. Our focus will be specifically on agent-based approaches which make use of negotiation metaphor for problem solving. It is safe to say that this emerging branch of operations research will find numerous applications in solving engineering and technology management problems.