A Combined Fuzzy Goal Programming and Big-Bang Big-Crunch Algorithm for Workforce Optimisation with Facility Layout Consideration

Abstract

Small scale enterprises constitute an important subset of manufacturing economy and the contribution of facility redesign in bridging the performance gaps in small-scale enterprises is necessary for enterprise growth and stability. In this paper, a biobjective programming-based facility layout design problem is formulated. We minimise workforce costs and maximise efficiency improvement in a layout. We utilised fuzzy goal programming and big-bang big-crunch algorithm in generating a Pareto solution. The model was tested using a small-scale sachet water production enterprise data. Increase in finished goods area was 66.55 % while reduction in total annual distance travelled in the facility was 48.22 % when the proposed layout was compared with the existing one. A reduction in annual cost of labour was 16.2 %. The possibility of using work-centres with high number of interrelationships was confirmed using the quality function deployment and Hurwicz's criterion. The optimal workforce size was found to be 14 workers against the existing workforce strength of 18 workers. The study provides a framework upon which small-scale sachet water production factories can be designed for optimum performance.

Study Of Fuzzy Goal Programming Model To Production Planning Problems Approach

“…The stages for the formulation of the fuzzy goal programming model were propose [18][19] [20] [21], among others: (1) Determine the decision variables, (2) Determine the forms of constraints, (3) Forming of linear program models based on the established objective and constraint functions, (4) Finding the optimal solution for each models, (5) Forming the membership function of the optimal solution according to the fuzzy membership function, (6) Forming of fuzzy goal programming model [22]. Furthermore, the fuzzy goal programming model is applied to the case with small medium enterprise (SME) to evaluate the model that has been made, the results are tested [23][24] [25]. The results of the application in the case of SME following the model with fuzzy goal programming that has been built then analyzed to see how the results of the optimum solution in production planning for SME's are applied.…”

Facility Layout optimization through Quality Function Deployment

“…Another approach suggests the implementation of the firefly algorithm approach for FLD in order to reduce the material handling costs [10]. There has also been concern regarding the possibility of implementing fuzzy logic for workforce optimization while taking into account facility layout [11].…”

Target-Oriented Compromised Sales and Profit Approach for Production and Distribution Planning in a Supply Chain

“…It is not possible to achieve the best values for all objectives at the same time. When there are targets or goals to be achieved for each objective, a goal programming (GP) technique can be used to determine compromised solutions (Broz et al, 2019;Da Silva & Marins, 2014;Ighravwe & Oke, 2015). When decision makers consider that objectives have different weights, the compromised solutions can be determined by maximizing a weighted average of satisfactions of all objectives (Javadian et al, 2009).…”