The paper presents an integrated production planner and job shop scheduler system with flexible modeling capabilities and powerful, scalable solution methods. The system generates close-to-optimal production and capacity plans on the medium term, and detailed production schedules on the short-term. However, the constraint-based, deterministic scheduling model can hardly account for all the unce...

This paper tackles the flexible job-shop scheduling problem with uncertain processing times. The uncertainty in processing times is represented by means of fuzzy numbers, hence the name fuzzy flexible job-shop scheduling. We propose an effective genetic algorithm hybridised with tabu search and heuristic seeding to minimise the total time needed to complete all jobs, known as makespan. To build...

This paper addresses the flexible job shop scheduling problem with minimization of the makespan, maximum machine workload, and total machine workload as the objectives. A multiobjective memetic algorithm is proposed. It belongs to the integrated approach, which deals with the routing and sequencing sub-problems together. Dominance-based and aggregation-based fitness assignment methods are used ...

For the Multi-Objective Flexible Job Shop Scheduling Problems (MOFJSSP), various optimization models have been designed. In the first part of the research (published in no. 2/2012) we presented the multi-sort production systems, the theoretical aspects of MOFJSSP framework, a specific real JSS process in drugs industry based on over 600 tasks to be optimally scheduled (used as a case study for ...

Flexible job-shop scheduling problem (FJSP) is an extension of the classical job-shop scheduling problem. FJSP is NP-hard and mainly presents two difficulties. The first one is to assign each operation to a machine out of a set of capable machines, and the second one deals with sequencing the assigned operations on the machines. This paper proposes a parallel variable neighborhood search (PVNS)...

Flexible assembly job shop scheduling has been proved to be an NP-hard problem. To reduce the complexity, it is always divided into 2 sub-problems: routing sub-problem and sequencing sub-problem. In this paper, in order to develop a solution with high accuracy, we propose a method that can deal with these two sub-problems concurrently. Tabu search, one of the meta-heuristics, is adopted. Some e...

In this paper flexible job-shop scheduling problem (FJSP) is studied in the case of optimizing different contradictory objectives consisting of: (1) minimizing makespan, (2) minimizing total workload, and (3) minimizing workload of the most loaded machine. As the problem belongs to the class of NP-Hard problems, a new hybrid genetic algorithm is proposed to obtain a large set of Paretooptimal s...

A meta-heuristic approach for solving the flexible job-shop scheduling problem (FJSP) is presented in this study. This problem consists of two sub-problems, the routing problem and the sequencing problem and is among the hardest combinatorial optimization problems. We propose a Evolutionary Algorithm (EA) for the FJSP. Our algorithm uses several different rules for generating the initial popula...

Flexible job-shop scheduling problem (FJSP) is an extended traditional job-shop scheduling problem, which more approximates to practical scheduling problems. This paper presents a multi-objective genetic algorithm (MOGA) based on immune and entropy principle to solve the multiobjective FJSP. In this improved MOGA, the fitness scheme based on Pareto-optimality is applied, and the immune and entr...