Flexible job-sop scheduling problem (FJSP) is based on the classical job-shop scheduling problem (JSP), however, it is even more harder than JSP because of the machine selection process in FJSP. In this paper, a particle swarm optimization (PSO) algorithm and a tabu search (TS) algorithm are integrated to solve the FJSP, the objective is to make the complete time minimum, i.e., to get the best ...

An extended version of the flexible job shop problem is tackled in this work. The considered extension to the classical flexible job shop problem allows the precedences between the operations to be given by an arbitrary directed acyclic graph instead of a linear order. Therefore, the problem consists of allocating the operations to the machines and sequencing them in compliance with the given p...

This paper presents a new algorithm based on integrating Genetic Algorithms and Tabu Search methods to solve the Job Shop Scheduling problem. The idea of the proposed algorithm is derived from Genetic Algorithms. Most of the scheduling problems require either exponential time or space to generate an optimal answer. Job Shop scheduling (JSS) is the general scheduling problem and it is a NP-compl...

In this paper a hybrid genetic and harmony search algorithm is proposed to find the possible best sequence of operation solutions for hybrid flow shop scheduling problems. In this work the problem is considered with respect to the objective of minimization of makespan. Hybrid flow shop scheduling problem is considered for the sequencing of jobs in a hybrid flow shop with two or more identical m...

In the classical job shop scheduling problem (JSSP), n jobs are processed to completion on m unrelated machines. Each job requires processing on each machine exactly once. For each job, technology constraints specify a complete, distinct routing which is fixed and known in advance. Processing times are sequence-independent, fixed, and known in advance. Each machine is continuously available fro...

Scheduling for the flexible job shop is very important in both fields of production management and combinatorial optimization. However, it quit difficult to achieve an optimal solution to this problem with traditional optimization approaches owing to the high computational complexity. The combining of several optimization criteria induces additional complexity and new problems. In this paper, a...

in some industries as foundries, it is not technically feasible to interrupt a processor between jobs. this restriction gives rise to a scheduling problem called no-idle scheduling. this paper deals with scheduling of no-idle open shops to minimize maximum completion time of jobs, called makespan. the problem is first mathematically formulated by three different mixed integer linear programming...

In this paper, we analyze the characteristics of the dynamic job shop scheduling problem when machine breakdown and new job arrivals occur. A hybrid approach involving neural networks(NNs) and geneticalgorithm(GA) is presented to solve the dynamic job shop scheduling problem as a static scheduling problem. The objective of this kind of job shop scheduling problem is minimizing the completion ti...

this study considers scheduling in hybrid flow shop environment with unrelated parallel machines for minimizing mean of job's tardiness and mean of job's completion times. this problem does not study in the literature, so far. flexible flow shop environment is applicable in various industries such as wire and spring manufacturing, electronic industries and production lines. after mode...

Flexible job shop scheduling problem, is an extension of the classical job shop scheduling problem. In Flexible job shop scheduling problem, there are more than one machine with the same features for the same purpose. The problem can be defined as appointing the jobs to the machines (assignment) and ordering the jobs at each machine (sequencing) to serve the desired purpose. Multi-objective fle...