چکیده:
In this paper, robust optimization of a bi-objective mathematical model in a dynamic cell formation problem considering labor utilization with uncertain data is carried out. The robust approach is used to reduce the effects of fluctuations of the uncertain parameters with regards to all the possible future scenarios. In this research, cost parameters of the cell formation and demand fluctuations are subject to uncertainty and a mixed-integer programming (MIP) model is developed to formulate the related robust dynamic cell formation problem. Then the problem is transformed into a bi-objective linear one. The first objective function seeks to minimize relevant costs of the problem including machine procurement and relocation costs, machine variable cost, inter-cell movement and intra-cell movement costs, overtime cost and labor shifting cost between cells, machine maintenance cost, inventory, holding part cost. The second objective function seeks to minimize total man-hour deviations between cells or indeed labor utilization of the modeled.
خلاصه ماشینی:
"formulated robust optimization of a mathematical model of a dynamic cell formation problem integrating CF, production planning and worker assignment that implemented with uncertain scenario-based data (Vafaeinezhad et al.
Sakhaeii and et al (2016) presented a robust optimization approach a new integrated mixed-integer linear programming (MILP) model to solve a dynamic cellular manufacturing system (DCMS) with unreliable machines and a production planning problem simultaneously.
1 the suggested robust optimization model In this paper, the overhead cost of the machine, the purchase cost of the machine, the revenue gained by machine sale, the variable cost of the machine, the cost of intercellular movement in each batch, the cost of intracellular movement in each batch, the cost of overtime of the machine, the cost of labor transportation between cells, the cost of machine movement, the cost of part inventory and the part demand parameter are considered uncertain and under scenario.
Analysis of the components of the objective function in different scenarios in three periods Total Cost Workload imbalanced Machine constant cost Machine variable cost Purchasing machine cost Inter cell movement Intra cell movement Inventory cost Overhead cost رجوع شود به تصویر صفحه Figure 1 shows the cell configuration in the first period for the main model of dynamic cell formation problem."