Flexible job-shop scheduling problem derived from the job-shop scheduling problem, and is more realistic than the job-shop scheduling problem in the manufacturing enterprise. It should be utilized with high efficiency. But it is a multi-objective optimal problem. Three minimization objectives (Maximum completion time (makespan), Total workload of machines and Workload of the critical machine) a...

Ideal schedules minimize both maximum completion time and total completion time of jobs. This paper presents polynomial-time algorithms finding ideal nonpreemptive and preemptive two-machine schedules of jobs with arbitrary release dates and precedence constraints and unit-execution-time operations on identical parallel machines, in a flow shop and an open shop. Heretofore, the complexity statu...

We consider the ow-shop scheduling problem. The objective is to schedule the jobs on the machines so that we minimize the time by which all jobs are completed. We studied and implemented diierent versions of the algorithm of Sevast'yanov based on linear programming to solve this problem. Using CPLEX, we did computational tests with random instances having up to 1000 jobs and 100 machines. If th...

This paper addresses the Hybrid Flow Shop (HFS) scheduling problems to minimize the total work-in-process inventory. Job scheduling problems are one of the oldest and real world combinational optimization problems. It is multi objective and complex in nature. There exist some criteria that must be taken into consideration when evaluating the quality of the proposed schedule. Consideration of jo...

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 job shop scheduling problem is one of the most arduous combinatorial optimization problems. Flexible job shop scheduling problem (FJSP) is an important extension of the classical job shop scheduling problem, where the same operation could be processed on more than one machine. This paper proposed a new effective approach based on the hybridization of the particle swarm optimization (PSO) an...

The Open-Shop Problem is a hard problem that can be solved using Constraint Programming or Operation Research methods. Existing techniques are efficient at reducing the search tree but they usually do not consider the absolute ordering of the tasks. In this work, we develop a new propagator for the One-Machine Non-Preemptive Problem, the basic constraint for the Open-Shop Problem. This propagat...

Although the deterministic flow shop model is one of the most widely studied problems in scheduling theory, its stochastic analog has remained challenging. No computationally efficient optimization procedure exists even for the general two-machine version. In this paper, we describe three heuristic procedures for the stochastic two-machine flow shop problem and report on computational experimen...

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...

The resource constraint project scheduling problem (RCPSP) is an NP-hard benchmark problem in scheduling which takes into account the limitation of resources’ availabilities in real life production processes and subsumes open-shop, job-shop, and flow-shop scheduling as special cases. We here present an application of machine learning to adapt simple greedy strategies for the RCPSP. Iterative re...