Ant colony optimisation for scheduling of flexible job shop with multi-resources requirements

The paper presents application of ant colony optimisation algorithm for scheduling multi-resources operations in flexible job shop type of production systems. Operations that require the participation of two or more resources are common in industrial practice, when planning are subject not only machines, but also other additional resources (personnel, tools, etc.). Resource requirements of operation are indicated indirectly by resource groups. The most important parameters of the resource model and resource groups are also described. A basic assumptions for ant colony algorithm used for scheduling in the considered model with multiresources requirements of operations is discussed. The main result of the research is the schema of metaheuristic that enables searching best-score solutions in manufacturing systems satisfying presented constraints.

[1]  Hartmut Schmeck,et al.  Ant colony optimization for resource-constrained project scheduling , 2000, IEEE Trans. Evol. Comput..

[2]  Jun Zhang,et al.  Ant Colony Optimization for Software Project Scheduling and Staffing with an Event-Based Scheduler , 2013, IEEE Transactions on Software Engineering.

[3]  John B. Shoven,et al.  I , Edinburgh Medical and Surgical Journal.

[4]  Gang Wang,et al.  Ant Colony Optimizations for Resource- and Timing-Constrained Operation Scheduling , 2007, IEEE Trans. Comput. Aided Des. Integr. Circuits Syst..

[5]  Deming Lei,et al.  Multi-objective production scheduling: a survey , 2009 .

[6]  Wojciech M. Kempa,et al.  A survey on methods of design features identification , 2015 .

[7]  Mehmet Mutlu Yenisey,et al.  A multi-objective ant colony system algorithm for flow shop scheduling problem , 2010, Expert Syst. Appl..

[8]  Andrea Rossi,et al.  Flexible job-shop scheduling with routing flexibility and separable setup times using ant colony optimisation method , 2007 .

[9]  Rong-Hwa Huang,et al.  Overlapping production scheduling planning with multiple objectives--An ant colony approach , 2008 .

[10]  Richard Y. K. Fung,et al.  Integrated process planning and scheduling by an agent-based ant colony optimization , 2010, Comput. Ind. Eng..

[11]  Adam Hamrol,et al.  New Method for Assessment of Raters Agreement Based on Fuzzy Similarity , 2015, SOCO.

[12]  Krzysztof Kalinowski,et al.  Preparatory Stages of the Production Scheduling of Complex and Multivariant Products Structures , 2015, SOCO.

[13]  Peng Wang,et al.  A Knowledge-Based Ant Colony Optimization for Flexible Job Shop Scheduling Problems , 2010, Appl. Soft Comput..

[14]  Aleksandar Lazinica New Advanced Technologies , 2010 .

[15]  Adeel Anjum,et al.  BangA: An Efficient and Flexible Generalization-Based Algorithm for Privacy Preserving Data Publication , 2017, Comput..

[16]  Christian Blum,et al.  An Ant Colony Optimization Algorithm for Shop Scheduling Problems , 2004, J. Math. Model. Algorithms.

[17]  Liang Gao,et al.  An effective hybrid algorithm for integrated process planning and scheduling , 2010 .

[18]  B. Chandra Mohan,et al.  A survey: Ant Colony Optimization based recent research and implementation on several engineering domain , 2012, Expert Syst. Appl..

[19]  Damian Krenczyk,et al.  ERP, APS and Simulation Systems Integration to Support Production Planning and Scheduling , 2015, SOCO.