A review of lot streaming in a flow shop environment with makespan criteria <s> Problem <s> Lot streaming is the process of splitting a job into sublots so that its operations can be overlapped. This paper deals with the problem of minimizing the length of a flow shop schedule when lot streaming is invoked. We show when it is sufficient in the one-job model to use the same sublot sizes for all machines, and we analyze the use of equal-sized sublots as a heuristic procedure. Finally, we demonstrate some of the difficulties involved in the n-job problem. <s> BIB001 </s> A review of lot streaming in a flow shop environment with makespan criteria <s> Problem <s> This paper treats the optimal lot streaming problem for multiple products in a two-machine flow shop with job setup times and sublot transfer times. If production lots are not preempted, an independent transfer lot sizing problem is obtained for each job; this problem is the same for any regular measure of performance. For continuous transfer lot sizes a closed-form optimal solution is obtained, while for integer valued lot sizes a fast polynomial algorithm is developed. The makespan minimization problem with lot streams is reduced to an equivalent two-machine makespan problem without lot streams or setup/transfer times but with modified processing times, and can thus be solved by Johnson's algorithm. The procedures are illustrated in an example. <s> BIB002 </s> A review of lot streaming in a flow shop environment with makespan criteria <s> Problem <s> Lot streaming is moving some portion of a process batch ahead to begin a downstream operation. The problem to be considered in this paper is the following: a single job consisting of U units is to be processed on two machines in the given order. Given a fixed number of possible transfer batches between the two machines, the problem is to find the timing and the size of the transfer batches (or, sublots) so as to optimize a given criterion. The schedules can be evaluated based on job completion, sublot completion, or item completion times. In the single job lot streaming problem, minimizing job completion time corresponds to minimizing the makespan, for which formulas for optimal sublot sizes are available. In this paper, the results for the sublot and item completion time models are presented. <s> BIB003 </s> A review of lot streaming in a flow shop environment with makespan criteria <s> Problem <s> We consider the problem of minimizing makespan in two-machine no-wait flowshops with multiple products requiring lot streaming. A “product” (or lot) consists of many identical items. Lot streaming (lot sizing) is the process of creating sublots (or transfer batches) to move the completed portion of a production sublot to downstream machines so that operations can be overlapped. The number of sublots for each product is fixed. When the flowshop produces only a single product, we obtain optimal continuous-sized sublots. It is shown that these sublot sizes are also optimal for the problem of simultaneous lot streaming and scheduling of multiple products. The optimal scheduling of products can be accomplished by application of the algorithm due to Gilmore and Gomory [1]. Then, we devise an efficient heuristic for the problem of simultaneous lot streaming (finding optimal integer-sized sublots) and scheduling of multiple products. Computational results indicate that this heuristic can consistently deliver close-to-optimal solutions for the problem. A comparison of this heuristic is also made with a heuristic that first divides items belonging to each product into nearly equal-sized sublots and then constructs a schedule for such sublots. Finally, we extend our solution procedures to a traditional and more general lot streaming model, where the number of sublots for each product is a decision variable. <s> BIB004 </s> A review of lot streaming in a flow shop environment with makespan criteria <s> Problem <s> The objective of this paper is to propose and evaluate heuristic search algorithms for two-machine flow shop problem with multiple jobs requiring lot streaming that minimizes make span and total flow time. The two heuristic search algorithms evaluated Are tabu search algorithm (TABU) and simulated annealing (SA) algorithm. To create neighborhoods for SA, three perturbation schemes, viz. pair wise exchange, insertion and random insertion perturbation are used and the performance of these on the final schedule is also compared. A wide variety of data sets are randomly generated for comparative evaluation. The results indicate that TABU and SA perform almost similar for the objective of makespan and TABU performs better over SA for the objective of total flow time irrespective of the neighborhood creation schemes. <s> BIB005 </s> A review of lot streaming in a flow shop environment with makespan criteria <s> Problem <s> In this paper, two different approaches have been proposed for solving two machine flow shop problems with multiple jobs requiring lot streaming with the objectives of minimizing the makespan and the total flow time of jobs, A population based evolutionary algorithm that involves evolution during the search process and a single point local search met a heuristics that work on a single solution are proposed. The population based approach employs local search, after the genetic search is over, to improve the effectiveness of the search procedure and hence it is called hybrid evolutionary algorithm (HYBRID). A threshold accepting algorithm (TA) proposed in this paper is a single point local search metaheuristic. A job here implies many identical items. Lot streaming creates sub lots to move the completed portion of a production sub lots to down stream machine. Proposed algorithms are evaluated using a set of randomly generated test problems. Experimental results are presented for comparison <s> BIB006 </s> A review of lot streaming in a flow shop environment with makespan criteria <s> Problem <s> The objective of this paper is to propose and evaluate heuristic search algorithms for a two-machine flowshop problem with multiple jobs requiring lot streaming that minimizes makespan. A job here implies many identical items. Lot streaming creates sublots to move the completed portion of a production lot to second machine. The three heuristic search algorithms evaluated in this paper are Baker’s approach (Baker), genetic algorithm (GA) and simulated annealing (SA) algorithm. To create neighborhoods for SA, three perturbation schemes, viz., pair-wise exchange, insertion and random insertion are used, and the performance of these on the final schedule is also compared. A wide variety of data sets is randomly generated for comparative evaluation. The parameters for GA and SA are obtained after conducting sensitivity analysis. The genetic algorithm is found to perform well for lot streaming in the two-machine flowshop scheduling. <s> BIB007 </s> A review of lot streaming in a flow shop environment with makespan criteria <s> Problem <s> The process of splitting a job lot comprised of several identical units into transfer batches (some portion of the lot), and permitting the transfer of processed transfer batches to downstream machines, allows the operations of a job lot to be overlapped. The essence of this idea is to increase the movement of work in the manufacturing environment. In this paper, the scheduling of multiple job lots with unit sized transfer batches is studied for a two-machine flow-line cell in which a single transport agent picks a completed unit from the first machine, delivers it to the second machine, and returns to the first machine. A completed unit on the first machine blocks the machine if the transport agent is in transit. We examine this problem for both unit dependent and independent setups on each machine, and propose an optimal solution procedure similar to Johnson’s rule for solving the basic two-machine flowshop scheduling problem. <s> BIB008
Author ( For the 2/N/C/II/CV, we need to simultaneously obtain the best job sequence and the optimal sublot allocation (sublot starting and completion times). All the papers allowed intermittent idling. It was showed that it is not possible to solve the n-job problem simply by applying lot streaming individually to the single-job problem BIB001 . Several papers independently show that this problem it is decomposed into an easily identifiable sequence of single job problems, using continuous values, even with setup times BIB002 and transfer times  . Other authors have widely tackled the same problem using discrete values (2/N/C/II/DV) considering setup times BIB005 BIB007 BIB006 . Sublot attached and detached setup times were also considered BIB002 . It was -763-Journal of Industrial Engineering and Management -http://dx.doi.org/10. 3926/jiem.553 presented some closed form solutions for continuous sublots and a fast polynominally bounded search algorithm for discrete sublots. Other papers proposed the use of removal times  , of no-wait condition BIB004 or even allowing interleaving BIB008 . Using variable sublots in a 2/*/V problem, only a paper was founded. Due to the complexity that involves variable sublots, it calculated continuous values and it did not consider setup times BIB003 .