In this paper the Group Technology problem of grouping parts in families and machines in cells in order to convert a job shop production system to some pseudo ow shops is considered Several heuristic methods for solving Group Technology problem have been proposed in the literature in general not producing a ow shop in each cell unless a great number of extra machines is added We use known techn...

Recent sensor technologies have enabled the capture of users’ behavior data. Given the large amount of data currently available from sensor-equipped environments, it is important to attempt characterization of the sensor data for automatically modeling users in a ubiquitous and mobile computing environment. As described herein, we propose a method that predicts a customer model using features b...

This paper considers two-machine flow shop scheduling problems with machine availability constraints. When the processing of a job is interrupted by an unavailability period of a machine, we consider both the resumable scenario in which the processing can be resumed when the machine next becomes available, and the semi-resumable scenarios in which some proportion of the processing is repeated b...

This paper presents a novel approach to compute optimal machine, shop oor and shell space expansion times under uncertain customer demand. It considers multiple machine types and allows for positive lead times for each type. Demand is assumed to be nondecreasing in a \weak" sense. A polynomial time algorithm (FIFEX) is developed and shown to be eeective and eecient with an example from the Semi...

New complexity results are derived. It is shown that the two machine flow shop problem with a single server is NP-hard if either the setup times or the processing times are constant. Furthermore, polynomial algorithms are given for special cases in which both setup times and processing times are constant. Flow-shop problems with a single server are generalizations of classical flow-shop problem...

Flow-shop scheduling problem (FSP) deals with the scheduling of a set of jobs that visit a set of machines in the same order. The FSP is NP-hard, which means that an efficient algorithm for solving the problem to optimality is unavailable. To meet the requirements on time and to minimize the make-span performance of large permutation flow-shop scheduling problems in which there are sequence dep...

this paper considers a two-stage assembly flow shop problem (tafsp) where m machines are in the first stage and an assembly machine is in the second stage. the objective is to minimize a weighted sum of earliness and tardiness time for n available jobs. jit seeks to identify and eliminate waste components including over production, waiting time, transportation, inventory, movement and defective...

The n-job, m-machine flow shop scheduling problem is one of the most general job scheduling problems. This study deals with the multi objective optimization with the criteria of makespan minimization and minimization of total weighted flow time for the flow shop scheduling problem. The n-job mmachine problem is known to be NP hard problem, several meta heuristics have been applied so far in the...

Scheduling is a combinatorial problem with important impact on both industry and commerce. If it is performed well it yields time and efficiency benefits and hence reduces costs. Genetic Algorithms have been applied to solve several types of scheduling problems; Flow Shop, Resource, Staff and Line Balancing have all been tackled. However Jobshop Scheduling is the most common problem of interest...

Traditional flexible flow shop scheduling cannot adapt to the work processes with existence of parallel machines, and blocks or limits the processes with no-wait constraints. Firstly, according to the problem in NWBFFSSP, which minimizes the maximum time used in the flow shop, an optimal solving model has been designed to realize the flexible flow shop scheduling with multi constraints; besides...