Multi-objective job-shop scheduling with lot-splitting production

摘要

While focusing on lot splitting in the job-shop scheduling problem, this study attempts to minimize the weighted total of stock, machine idle and carrying costs. Stock cost is determined using processing time. Machine idle cost is estimated using machine idle time. Carrying cost is calculated using the carry number of lot splitting. Results of this study demonstrate that stock cost and machine idle cost are inversely related to the number of lots split and have marginal decreasing result of benefit. The benefit of processing time is not as apparent as that of count and increase in turn. Carrying cost is positively related to the number of lots split. The minimum weighted total cost of stock, machine idle and carrying costs typically appears when the number of lots split is 2 or 3. The ant colony optimization (ACO) algorithm is used to solve the job-shop scheduling problem. Compared with the solution obtained by LINGO, the ACO algorithm performs well in scheduling and uses less time to solve the problem.