This paper reviews modern genetic algorithm based approaches for solving job shop scheduling problems Genetic algorithms represent one of the most popular and mostly used metaheuristic methods applied for solving many optimization problems within last few decades. Job shop scheduling represents one of the hardest combinatorial optimization problems where number of possible schedules drastically...

This paper discusses the scheduling of precedence-related jobs non-preemptively in a job shop environment with an objective of minimizing the makespan. Due to the NP-hard nature of the scheduling problems, it is usually difficult to find an exact optimal schedule and hence one should rely on finding a near to optimal solution. This paper proposes a computationally effective powers-of-two heuris...

A general model for job shop scheduling is described which applies to static, dynamic and non-deterministic production environments. Next, a Genetic Algorithm is presented which solves the job shop scheduling problem. This algorithm is tested in a dynamic environment under different workload situations. Thereby, a highly efficient decoding procedure is proposed which strongly improves the quali...

This is a summary of the journal article (Malapert et al. 2012) published by Journal on Computing entitled “An Optimal Constraint Programming Approach to the Open-Shop Problem”. The article presents an optimal constraint programming approach for the Open-Shop scheduling problem, which integrates recent constraint propagation and branching techniques with new upper bound heuristics. Randomized r...

In this study, we consider the production environment of no-wait reentrant flow shop with the objective of minimizing makespan of the jobs. In a reentrant flow shop, at least one job should visit at least one of the machines more than once. In a no-wait flowshop scheduling problem, when the process of a specific job begins on the first machine, it should constantly be processed without waiting ...

reflect the temporal relationships between manufacturing activities and the capacity limitations of a set of shared resources. The allocation also affects a schedule's opti-mality with respect to criteria such as cost, lateness, or throughput. The globalization of manufacturing makes such optimization increasingly important. To survive in this competitive market, manufacturing enterprises must ...

In recent years, constraint propagation techniques have been shown to be highly eeective for solving diicult scheduling problems. In this paper, we present an algorithm which combines constraint propagation with a problem decomposition approach in order to simplify the solution of the job shop scheduling problem. This is mainly guided by the observation that constraint propagation is more eeect...

— Flexible Job Shop scheduling problem (FJSSP) is an important scheduling problem which has received considerable importance in the manufacturing domain. In this paper a genetic algorithm (GA) based scheduler is presented for flexible job shop problem to minimise makespan. The proposed approach implements a domain independent GA to solve this important class of problem. The scheduler is impleme...

A train scheduling problem in a single-track railway can be modeled as a job-shop scheduling problem. We use a mixed graph model for such a job-shop problem with appropriate criteria. There are several performance evaluations for a train schedule. Optimizing a train schedule subtends minimizing total tardiness of the trains, minimizing the sum of train transit times, minimizing the makespan for...