This paper presents an application of a fuzzy programming approach for multiple objectives to the aggregate production planning (APP). The parameters levels have been applied via a case study from the SMEs company in Thailand. The proposed model attempts to minimise total production cost and minimise the subcontracting units. Conventional harmony search algorithm (HSA) with its hybridisations of the global best harmony search (GHSA) and the variable neighbourhood search of the HSA (VHSA) are applied for fine aggregate production planning. Based on the experimental results, it can be concluded that the proposed VHSA is more effective than the other approaches in terms of superiority of solution and required CPU time. The basic idea is the change of neighbourhoods during searching for a better solution. The hybridisations proceed by a descent method to a local minimum exploring then, systematically or at random, increasingly distant neighbourhoods of this local solution. The proposed model yields an efficient compromise solution and the overall levels of decision making satisfaction with the multiple objectives.