This work studies the performance of two Mixed Integer Linear Programming (MILP) models to solve scheduling problems in a flexible job shop environment with recirculation and assembly using a due-date-based objective function. The models convey different approaches both in the modelling of time (discrete and continuous approaches) as well as in the assignment of jobs to machines. The comparison...

The stochastic job shop scheduling problem (SJSSP) is a kind of stochastic programming problem which transformed from job shop scheduling problem. The SJSSP is an NP-hard problem. Current solutions for the SJSSP can be classified as analytic and heuristic. However, these two methods ignored characteristics of SJSSP, which lead to large computation times and inefficient solutions. In order to ef...

In manufacturing systems, there are environments where the elaboration of a product requires series sequential operations, involving configuration machines by stages, intermediate buffer capacities, definition assembly lines, and routing parts. The objective this research is to develop modeling statistical analysis complexity in systems under flow shop hybrid environments. methodological approa...

in this paper, a new approach to overlapping operations in job shop scheduling is presented. in many job shops, a customer demand can be met in more than one way for each job, where demand determines the quantity of each finished job ordered by a customer. in each job, embedded operations can be performed due to overlapping considerations in which each operation may be overlapped with the other...

Original scientific paper This paper presents a hybrid genetic algorithm for assembly flow-shop scheduling problem with sequence-dependent setup and transportation times, with objectives, namely the minimizing of weighted, sum of total weighted squared tardiness, makespan, and total weighted squared earliness and number of tardy jobs. Since the problem is NP-hard, we solved this problem by hybr...

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...

In simple flow shop problems, each machine operation center includes just one machine. If at least one machine center includes more than one machine, the scheduling problem becomes a flexible flow-shop problem. Recently, group scheduling has also been proposed and discussed. In the group scheduling, each job belongs to a specific group and all the jobs are processed group by group. In this pape...

Genetic algorithms are a very popular heuristic which have been successfully applied to many optimization problems within the last 30 years. In this chapter, we give a survey on some genetic algorithms for shop scheduling problems. In a shop scheduling problem, a set of jobs has to be processed on a set of machines such that a specific optimization criterion is satisfied. According to the restr...

This paper studied the flow shop scheduling problem under machine availability constraints. The machines are subject to flexible preventive maintenance activities. The nonresumable scenario for the jobs was considered. That is, when a job is interrupted by an unavailability period of a machine it should be restarted from the beginning. The objective is to minimize the total tardiness time for t...

In this work, multicriteria decision making objective for flow shop scheduling with sequence dependent set up time and due dates have been developed. Multicriteria decision making objective includes total tardiness, total earliness and makespan simultaneously which is very effective decision making for scheduling jobs in modern manufacturing environment. As problem of flow shop scheduling is NP...