A New Algorithm for Large-Scale Scheduling Problems:  Sequence Branch Algorithm

Abstract

Mixed integer linear programming based methods have been widely employed but have been limited to problems with simple recipes or small-scale scheduling problems. This paper proposes the sequence branch algorithm (SBA) that can handle large-scale complex scheduling problems for batch processes under unlimited intermediate storage policy. The SBA generates the schedule tree in which all feasible schedules are included. A heuristic function is employed to accelerate the searching speed and it causes the results somewhat deviated from the optimal solution. The efficiency of the proposed algorithm is illustrated through complex and large-scale problems including a case study of a semiconductor fabrication process.

Scheduling a Single-Product Reentrant Process with Uniform Processing Times

“…Another approach has been to use a heuristic method, viz. sequence branch algorithm, proposed by Lee et al 10 This method views the problem as that of scheduling constituent tasks and evaluates promising partial sequences of these tasks. It is essentially a specialized branch-and-bound technique that also quickly becomes computationally very expensive.…”

“…Having illustrated our algorithm on a simple example, we now take a more complex process and use our algorithm in both deterministic and stochastic environments. Furthermore, we compare it with the SBA of Lee et al 10 and analyze the impact of the lot release time interval on various system performance criteria.…”

“…For this example, the absolute minimum residence time is 67.3 h, and the minimum cycle time is 1.8 h. First, we compare the performances of our algorithm and the SBA. 10 Comparison with the SBA. For this comparison, we vary N from 5 to 100 and assume that all lots are available for release into an empty plant at zero time.…”

“…Lee et al 10 attempted the scheduling of the above aggregate model of Lu et al 9 as an example for their new heuristic sequence branch algorithm (SBA). In contrast to other works, they assumed a deterministic environment and did not use discrete-event simulation.…”

“…They found local search procedures to be quite effective for the sequence generation step. However, except for the work of Lee et al, 10 no one has explicitly addressed network flowshops with reentrant flows.…”