We consider the problem of scheduling n jobs onm identical parallel batching machines. Each job is characterized by a release time and a processing time. Each machine can process up to B (B < n ) jobs as a batch simultaneously. The processing time of a batch is equal to the largest processing time among all jobs in the batch. The objective is to minimize the maximum completion time (makespan). ...

making a rational decision about the free production capacity of a firm requires accurate and comprehensive information in different fields such as unscheduled time of the machines, materials or other required resources status in the firm and the related supply chain. in this study, we try to achieve the needed information through integrating advanced available-to-promise mechanism with schedul...

Based on MATLAB/SimEvents simulation platform and genetic algorithm, the simulation and optimization of energy consumption in hybrid flow shop is studied. Considering workshop layout and workpiece path, machining process simulation in hybrid flow shop is realized. With the processing time, processing power and stand-by power introduced into simulation model, the energy consumption simulation in...

This paper presents a reducedcomplexity algorithm for exactly solving two-job shop scheduling problems where an arbitrary number of non-availability periods may occur on each of the m machines (m > 2). Considering the limited availability of machines makes the scheduling models more realistic in comparison to usual ones. The proposed solution algorithm is an extension of the geometric approach ...

This paper provides a heuristic procedure for solving the constrained flow-shop scheduling problems of n-jobs on m-machines. We obtained a schedule with a set of n-jobs to minimize the mean weighted flow-time. This method is very easy to understand and to apply. It will also help managers in the scheduling related issues by aiding them in the decision making process and providing an optimal or ...

tendency to optimization in last decades has resulted in creating multi-product manufacturing systems. production planning in such systems is difficult, because optimal production volume that is calculated must be consistent with limitation of production system. hence, integration has been proposed to decide about these problems concurrently. main problem in integration is how we can relate pro...

In this paper, we propose a neuro-genetic decision support system coupled with simulation to design a job shop manufacturing system by achieving predetermined values of targeted performance measures such as flow time, number of tardy jobs, total tardiness and machine utilization at each work center. When a manufacturing system is designed, the management has to make decisions on the availabilit...

In this study, a distributed flow shop scheduling problem with batch delivery constraints is investigated. The objective to minimize the makespan and energy consumptions simultaneously. To end, hybrid algorithm combining wale optimization (WOA) local search heuristics developed. proposed algorithm, each solution represented by three vectors, namely job sequence vector, assignment factory vector...

This paper considers some permutation flow shop scheduling problems with a learning effect on no-idle dominant machines. The objective is to minimize maximum completion time. This objective is considered under following dominant machines constraint: idm, ddm, idm–ddm and ddm–idm. We present a polynomial-time solution algorithm for each of the above cases. 2006 Elsevier Inc. All rights reserved.