Tabu search based solution approaches for lot streaming problems in flow shops

Lot streaming (LS) splits the production lot into sublots, and schedules these sublots in an overlapping way on the machines in order to accelerate the process of orders and improve the overall system performance.In this thesis, a number of LS problems all of which aim to minimize makespan in multi machine flow shops are investigated. First problem considers a single-product case in stochastic flow shops. For this problem, a solution approach that integrates tabu search (TS) and simulation is proposed. Sublot size configurations are searched via TS and stochastic behavior of the system is handled by simulation.Remaining three problems differ from each other by sublot types and divisibility of sublot sizes and deal with multi-product cases in deterministic flow shops. Entire problem is partitioned into sequencing and sublot allocation sub-problems. For sequencing sub-problem, a number of simple and efficient sequencing heuristics developed for general flow shops are modified according to LS requirements. For sublot allocation sub-problem, mixed integer programming (MIP) based approaches are proposed. For entire problem, a hybrid solution approach which uses the best sequencing heuristic (i.e., NEH(D,TPLS)) in sequencing sub-problem and applies MIP-based approaches for sublot allocation sub-problem, is proposed. Proposed hybrid approach not only gives efficient results for small/medium sized problems in short computation times but also solves large-sized problems in reasonable times. Finally, to improve solution quality in small/medium sized problems, same approach is also integrated to a solution procedure where initial sequence is taken as NEH(D,TPLS) and alternative sequences are evaluated via TS.