A linear programming embedded simulated annealing in the design of distributed layout with production planning and systems reconfiguration

In this paper, a linear programming embedded simulated annealing algorithm for solving a comprehensive model in the design and operation of distributed layout -based manufacturing systems is presented. The mathematical model considered incorporates a number of important manufacturing attributes. These attributes include demand fluctuation, system reconfiguration, lot splitting, work load balancing, alternative routing, machine capability, tooling requirements, material handling cost, machine relocation cost, setup cost, inventory carrying cost, in-house production, and subcontracting costs. Optimal solutions for such comprehensive mathematical models can only be found for small size problems due to NP-complexity. To solve the model for large size problems, efficient meta-heuristic algorithm is required. The development of such an algorithm is the main contribution of this paper. Numerical examples are presented to demonstrate the computational performance of the developed algorithm and illustrate a challenge that may be encountered when one tries to embed a linear programming in a metaheuristic.