Flow shop scheduling problem has a wide application in the manufacturing and has attracted much attention in academic fields. From other point, on time delivery of products and services is a major necessity of companies’ todays; early and tardy delivery times will result additional cost such as holding or penalty costs.  In this paper, just-in-time (JIT) flow shop scheduling problem with preemp...

In this paper, we address the problem of production systems having two characteristics. First, the manufacturing times can be chosen between given bounds. Such a production system is said to have controllable processing times. Second, an operation must start as soon as the previous operation on the same part (if any) is completed. A production system having this characteristic is said to be no-...

Many real time processes have complex, uncertain and nonlinear dynamics. Boilers are nonlinear, time varying, multi-input multi-output (MIMO) systems, whose states generally vary with operating conditions. The major problem in controlling that system is that its drum water pressure and steam flow dynamics include an integrator that results a critically stable behavior. Conventional controller p...

This paper proposes an effective multi-objective differential evolution algorithm (MDES) to solve a permutation flow shop scheduling problem (PFSSP) with modified Dejong's learning effect. The proposed algorithm combines the basic differential evolution (DE) with local search and borrows the selection operator from NSGA-II to improve the general performance.  First the problem is encoded with a...

This paper presents an investigation of scheduling procedures to seek the minimum of a positively weighted convex sum of makespan and the number of tardy jobs in a static flexible flow shop scheduling environment. The flexible flow shop problem is a scheduling of jobs in a flow shop environment consisting of series of production stages, some of which may have only one machine, but at least one ...

In this paper, we address the problem of finding a permutation schedule of n jobs in an m machine flow-shop environment that minimizes the maximum completion time Cmax (Makespan) of all jobs. The jobs are available at time zero and have sequence-dependent setup times on each machine. All parameters, such as processing and setup times, are assumed to be known with certainty. This problem is clas...

The Shifting Bottleneck (SB) heuristic is among the most successful approximation methods for solving the Job Shop problem. It is essentially a machine based decomposition procedure where a series of One Machine Sequencing Problems (OMSPs) are solved. However, such a procedure has been reported to be highly ineffective for the Flow Shop problems (Jain and Meeran 2002). In particular, we show th...

Lot sizing and scheduling in flow shop has been considered in this paper. Our study includes a multi-level and multi-period capacitated lot sizing and scheduling problem (CLSP) with sequence-dependent setups, setups carry over in flow shop. In manufacturing environments backlogging is unavoidable. If the production capacity is infinite, any demand can be satisfied