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...

In the job shop scheduling problem (JSP), a finite set of jobs is processed on a finite set of machines. Each job is characterized by a fixed order of operations, each of which is to be processed on a specific machine for a specified duration. Each machine can process at most one job at a time and once a job initiates processing on a given machine it must complete processing uninterrupted. A sc...

The Group Shop Scheduling Problem (GSP) is a generalization of the classical Job Shop and Open Shop Scheduling Problems. In the GSP there are m machines and n jobs. Each job consists of a set of operations, which must be processed on specified machines without preemption. The operations of each job are partitioned into groups on which a total precedence order is given. The problem is to order t...

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...

In this paper we deal with solution algorithms for a general formulation of the job shop problem, called alternative graph. We study in particular the job shop scheduling problem with blocking and/or no-wait constraints. Most of the key properties developed for solving the job shop problem with infinite capacity buffer do not hold in the more general alternative graph model. In this paper we re...

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...

Planning and scheduling problems in various industrial environments are combinatorial and very difficult. Generally, it is extremely hard to solve these types of problems in their general form. Scheduling can be formulated as a problem of determining the best sequence to execute a set of tasks on a set of resources, respecting specific constraints like precedence or disjunctive constraints (Car...

This paper presents a new approach to genetic algorithm based scheduling. We use genetic algorithms augmented with a case-based memory, containing population members from past problem solving attempts, to obtain better performance over time on sets of similar job shop scheduling problems. Rather than starting with a randomly initialized population on each scheduling problem, we periodically inj...