Ant Colony Algorithm for Just-in-Time Job Shop Scheduling with Transportation Times and Multirobots

Abstract

Handling rapidly evolving technology and almost daily changes in demand and customer satisfaction, while maintaining competitiveness in a highly competitive environment, requires good coordination and planning of both production and logistics activities on the shop floor, namely: machines and tools. The goal is to optimize costs and reduce delivery lead times in order to provide the customer just in time; we focus on the job shop scheduling problem (JSSP), which is one of the most complex problems encountered in real shop floor. In this paper, we study a generalized (JSSP) including transportation times and a set of additional constraints on the number of transporter vehicles and their multiple transfer capabilities and also on the limited capacity of input/output of machines. The objective is to minimize in one hand tardiness and earliness penalties on delays and advances compared to the lead-time delivery of finished jobs and on the other hand the number of empty moves of transporter vehicles.

Reducing myopic behavior in FMS control: A semi-heterarchical simulation–optimization approach

“…Generally speaking, when JIT production objectives are considered, the scheduling models in the literature assume a linear relationship between earliness and tardiness costs (Guo et al, 2008;Sun et al, 2010;Gomes et al, 2005;El Khoukhi et al, 2011). Nevertheless, simply minimizing tardiness costs, or the linear combination of earliness and tardiness, is too simplistic since tardiness costs comprise other qualitative indicators related to customer loyalty (i.e., customer dissatisfaction and the risk of losing the customer).…”