The job shop problem is an important part of scheduling in the manufacturing industry. A new intelligent algorithm named Shuffled Complex Evolution (SCE) algorithm is proposed in this paper with the aim of getting the minimized makespan. The sequence mapping mechanism is used to change the variables in the continuous domain to discrete variables in the combinational optimization problem; the se...

The flexible job shop scheduling problem (FJSP) is a generalization of the classical job shop scheduling problem that allows to process operations on one machine out of a set of alternative machines. The FJSP is an NP-hard problem consisting of two sub-problems, which are the assignment and the scheduling problems. In this paper, we propose how to solve the FJSP by hybrid metaheuristics-based c...

A job-shop scheduling problem is one of the classic scheduling problems considered to be NP-hard. In this paper, we presenta modified adaptiveevolutionary algorithm (EA) that uses speculative mutations, variable fitness functions and a pseudo-random number generator for solving job-shop scheduling problems. The algorithm was tested on well-known benchmark datainstances, such as Ft10, La01, Swv0...

The paper considers the dynamic job shop scheduling problem (DJSSP) with job release dates which arises widely in practical production systems. The principle characteristic of DJSSP considered in the paper is that the jobs arrive continuously in time and the attributes of the jobs, such as the release dates, routings and processing times are not known in advance, whereas in the classical job sh...

  In this paper, we consider a flow shop scheduling problem with bypass consideration for minimizing the sum of earliness and tardiness costs. We propose a new mathematical modeling to formulate this problem. There are several constraints which are involved in our modeling such as the due date of jobs, the job ready times, the earliness and the tardiness cost of jobs, and so on. We apply adapte...

In the stochastic online scheduling environment, jobs with unknown release times and weights arrive over time. Upon arrival, the information on the weight of the job is revealed but the processing requirement remains unknown until the job is finished. With the objective of minimizing the total weighted completion time, various asymptotically optimal algorithms have been proposed for the online ...

A data mining based approach to discover previously unknown priority dispatching rules for job shop scheduling problem is presented. This approach is based upon seeking the knowledge that is assumed to be embedded in the efficient solutions provided by the optimization module built using tabu search. The objective is to discover the scheduling concepts using data mining and hence to obtain a ru...

In this paper we consider a job shop scheduling problem with blocking (zero buffer) constraints. Blocking constraints model the absence of buffers, whereas in the traditional job shop scheduling model buffers have infinite capacity. There are two known variants of this problem, namely the blocking job shop scheduling (BJSS) with swap allowed and the BJSS with no-swap. A swap is needed when ther...

The Flexible Job Shop scheduling Problem (FJSP) is a generalization of the classical Job Shop Problem in which each operation must be processed on a given machine chosen among a finite subset of candidate machines. The aim is to find an allocation for each operation and to define the sequence of operations on each machine so that the resulting schedule has a minimal completion time. We propose ...

The majority of the research using evolutionary algorithms for the Job Shop Scheduling Problem (JSSP) has studied only the static JSSP. Few evolutionary algorithms have been applied to the Dynamic Job Shop Scheduling Problem (DJSSP) which is more similar to real-world applications. We implement a hybrid genetic algorithm for solving the dynamic job shop problem. A direct chromosome representati...