A jssp solution for production planning optimization combining industrial engineering and evolutionary algorithms

Shop Scheduling ◽

Planning Optimization

A Job Shop Scheduling Problem (JSSP), where p processes and n jobs should be processed on m machines so that the total completion time is minimal, is a well-known problem with many industrial applications. Many researchers focus on the JSSP classification and algorithms that address the different JSSP classes. In this research work, the production times, a very well-known theme covered in Industrial Engineering (IE), are integrated into an Evolutionary Algorithm (EA) to solve real-world JSSP problems. Since a drawback of classical IE is a manual determination of the technological times, an Internet of Things (IoT) architecture is proposed as a possible solution.

Optimizing the Low-Carbon Flexible Job Shop Scheduling Problem with Discrete Whale Optimization Algorithm

Mathematics ◽

10.3390/math7080688 ◽

2019 ◽

Vol 7 (8) ◽

pp. 688 ◽

Cited By ~ 6

Author(s):

Fei Luan ◽

Zongyan Cai ◽

Shuqiang Wu ◽

Shi Qiang Liu ◽

Yixin He

Keyword(s):

Completion Time ◽

Job Shop ◽

Job Shop Scheduling ◽

Flexible Job Shop ◽

Low Carbon ◽

Exploration And Exploitation ◽

Shop Scheduling ◽

Whale Optimization

The flexible job shop scheduling problem (FJSP) is a difficult discrete combinatorial optimization problem, which has been widely studied due to its theoretical and practical significance. However, previous researchers mostly emphasized on the production efficiency criteria such as completion time, workload, flow time, etc. Recently, with considerations of sustainable development, low-carbon scheduling problems have received more and more attention. In this paper, a low-carbon FJSP model is proposed to minimize the sum of completion time cost and energy consumption cost in the workshop. A new bio-inspired metaheuristic algorithm called discrete whale optimization algorithm (DWOA) is developed to solve the problem efficiently. In the proposed DWOA, an innovative encoding mechanism is employed to represent two sub-problems: Machine assignment and job sequencing. Then, a hybrid variable neighborhood search method is adapted to generate a high quality and diverse population. According to the discrete characteristics of the problem, the modified updating approaches based on the crossover operator are applied to replace the original updating method in the exploration and exploitation phase. Simultaneously, in order to balance the ability of exploration and exploitation in the process of evolution, six adjustment curves of a are used to adjust the transition between exploration and exploitation of the algorithm. Finally, some well-known benchmark instances are tested to verify the effectiveness of the proposed algorithms for the low-carbon FJSP.

Modeling and Simulation of Holonic Meta-Algorithm in Scheduling Process Using PERT Technique − Optimization in Job Shop Scheduling Problem

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.760.199 ◽

2015 ◽

Vol 760 ◽

pp. 199-204

Author(s):

Mircea Gorgoi ◽

Corneliu Neagu

Keyword(s):

Objective Function ◽

Job Shop ◽

Job Shop Scheduling ◽

Scheduling Problem ◽

New Approach ◽

Shop Scheduling ◽

Technique Optimization ◽

Optimum Solution

In generally scheduling can be viewed as optimization, bound by sequence and resource constrain and the minimization of the makespan is often used as the criterion. In this paper minimization of the makespan or complete time will be used such as an objective function and not the criterion of the decision. The new approach use heuristic elementary priority dispatch rules as the criterion of the decision. This research purpose a new methodology which use a specific elements of PERT techniques to find the optimum solution. New approach establish a solution's space where are find the all solution of the problem. Determination of the solution's space is realized by a meta-algorithm which take in account all the variant of the solutions of the process.

A hybrid genetic Tabu search algorithm for minimising total completion time in a flexible job-shop scheduling problem

European J of Industrial Engineering ◽

10.1504/ejie.2020.112479 ◽

2020 ◽

Vol 14 (6) ◽

pp. 763

Author(s):

Asma Fekih ◽

Hatem Hadda ◽

Imed Kacem ◽

Atidel B. Hadj Alouane

Keyword(s):

Completion Time ◽

Job Shop ◽

Job Shop Scheduling ◽

Search Algorithm ◽

Flexible Job Shop ◽

Tabu Search Algorithm ◽

Scheduling Problem ◽

Shop Scheduling

Petri Net and GA Based Method for JSP Optimization with Dual-Objective

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.121-126.4547 ◽

2011 ◽

Vol 121-126 ◽

pp. 4547-4551

Author(s):

Li Xin Qi ◽

Ze Tao

Keyword(s):

Petri Net ◽

Supervisory Control ◽

Completion Time ◽

Job Shop ◽

Job Shop Scheduling ◽

Linear Constraint ◽

Scheduling Problem ◽

Shop Scheduling ◽

Scheduling Method

A new dual-objective scheduling method based on the controlled Petri net and GA is proposed to the job-shop scheduling problem (JSP) constrained by machines, workers. Firstly, a detailed analysis of supervisory control for Petri net with uncontrollable transitions, especially important, for OR-logics linear constraint, a new method for constructing a Petri net feedback controller based on monitor and inhibitor arcs is presented. The Petri net model is constructed based on above method in flexible JSP. Then, the genetic algorithm (GA) is applied based on the controlled Petri net model and Pareto. Function objectives of the proposed method are to minimize the completion time and the total expense of machines and workers. Finally, Scheduling example is employed to illustrate the effectiveness of the method.

Petri Net with Uncontrollable Transition and GA Based Approach for JSP

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.48-49.824 ◽

2011 ◽

Vol 48-49 ◽

pp. 824-829

Author(s):

Tao Ze ◽

Xiao Xia Liu

Keyword(s):

Petri Net ◽

Completion Time ◽

Job Shop ◽

Job Shop Scheduling ◽

Flexible Job Shop ◽

Scheduling Problem ◽

Shop Scheduling ◽

Scheduling Method

A new dual-objective scheduling method based on the controlled Petri net and GA is proposed to the job-shop scheduling problem (JSP) with urgent orders constrained by machines, workers. Firstly, a controller designed method for Petri net with uncontrollable transition is introduced, and based on the method, the Petri net model is constructed for urgent jobs in flexible job shop scheduling problem. Then, the genetic algorithm (GA) is applied based on the controlled Petri net model and Pareto. Function objectives of the proposed method are to minimize the completion time and the total expense of machines and workers. Finally, Scheduling example is employed to illustrate the effectiveness of the method.

Memetic chicken swarm algorithm for job shop scheduling problem

International Journal of Electrical and Computer Engineering (IJECE) ◽

10.11591/ijece.v9i3.pp2075-2082 ◽

2019 ◽

Vol 9 (3) ◽

pp. 2075 ◽

Cited By ~ 3

Author(s):

Soukaina cherif bourki Semlali ◽

Mohammed Essaid Riffi ◽

Fayçal Chebihi

Keyword(s):

Completion Time ◽

Job Shop ◽

Job Shop Scheduling ◽

Scheduling Problem ◽

Swarm Optimization ◽

Shop Scheduling ◽

Swarm Algorithm ◽

Chicken Swarm Optimization

<p>This paper presents a Memetic Chicken swarm optimization (MeCSO) to solve job shop scheduling problem (JSSP). The aim is to find a better solution which minimizes the maximum of the completion time also called Makespan. In this paper, we adapt the chicken swarm algorithm which take into consideration the hierarchical order of chicken swarm while seeking for food. Moreover, we integrate 2-opt method to improve the movement of the rooster. The new algorithm is applied on some instances of ORLibrary. The empirical results show the forcefulness of MeCSO comparing to other metaheuristics from literature in term of run time and quality of solution.</p>

Application of dynamic firework algorithm considering variable neighborhood strategy in flexible job shop scheduling problem

E3S Web of Conferences ◽

10.1051/e3sconf/202126801062 ◽

2021 ◽

Vol 268 ◽

pp. 01062

Author(s):

Jie Lv ◽

Fenqiang Zhang

Keyword(s):

Completion Time ◽

Job Shop ◽

Job Shop Scheduling ◽

Flexible Job Shop ◽

Scheduling Problem ◽

Shop Scheduling ◽

Processing Cost ◽

Fitness Value

Aiming at the flexible job shop scheduling problem, this paper constructs a dual-objective mathematical model to minimize the maximum completion time and the minimum total processing cost. The traditional firework algorithm introduces a variable neighborhood search strategy, which is generated during the explosion of the algorithm. On the basis of explosive spark and Gaussian spark, the algorithm is further avoided from falling into the dilemma of local optimization. The product of completion time and processing cost is used as the fitness value of the plan, so that the firework algorithm is suitable for solving the two objective scheduling problems in this paper, and the ratio of fitness value and congestion is used as a comprehensive index for the selection of the optimal plan . In this paper, the selected 5×6 calculation examples are solved, and the completion time of the optimal scheduling scheme is reduced by 12.9%, and the total production cost is reduced by 17.67%, which verifies the feasibility and efficiency of the method.