Optimizing combination of job shop scheduling and quadratic assignment problem through multi-objective decision making approach

Multi-objective decision making and search space for the evaluation of production process schedulingOver the years, various approaches have been proposed in order to solve the multi-objective job-shop scheduling problem - particularly a hard combinatorial optimization problem. The paper presents an evaluation of job shop scheduling problem under multiple objectives (mean flow time, max lateness, mean tardiness, mean weighted tardiness, mean earliness, mean weighted earliness, number of tardy tasks). The formulation of the scheduling problem has been presented as well as the evaluation schedules for various optimality criteria. The paper describes the basic mataheuristics used for optimization schedules and the approaches that use domination method, fuzzy method, and analytic hierarchy proccess (AHP) for comparing schedules in accordance with multiple objectives. The effectiveness of the algorithms has been tested on several examples and the results have been shown. New search space for evaluation and generation of schedules has been created. The three-dimensional space can be used for the analysis and control of the production processes.

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A multi-objective decision-making framework using preference selection index for assembly job shop scheduling problem

International Journal of Management Concepts and Philosophy ◽

10.1504/ijmcp.2016.10000591 ◽

2016 ◽

Vol 9 (4) ◽

pp. 362

Author(s):

Midhun Paul ◽

T. Radha Ramanan ◽

R. Sridharan

Keyword(s):

Decision Making ◽

Job Shop ◽

Job Shop Scheduling ◽

Selection Index ◽

Scheduling Problem ◽

Job Shop Scheduling Problem ◽

Shop Scheduling ◽

Multi Objective ◽

Decision Making Framework

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Many-objective flexible job shop scheduling using NSGA-III combined with multi-attribute decision making

Modern Physics Letters B ◽

10.1142/s0217984918401103 ◽

2018 ◽

Vol 32 (34n36) ◽

pp. 1840110 ◽

Cited By ~ 1

Author(s):

Chun Wang ◽

Zhicheng Ji ◽

Yan Wang

Keyword(s):

Decision Making ◽

Job Shop ◽

Job Shop Scheduling ◽

Optimization Problems ◽

Reference Points ◽

Flexible Job Shop ◽

Flexible Job Shop Scheduling ◽

Shop Scheduling ◽

Multi Objective ◽

Multi Attribute Decision Making

This paper considers many-objective flexible job shop scheduling problem (MaOFJSP) in which the number of optimization problems is larger than three. An integrated multi-objective optimization method is proposed which contains both optimization and decision making. The non-dominated sorting genetic algorithm III (NSGA-III) is utilized to find a trade-off solution set by simultaneously optimizing six objectives including makespan, workload balance, mean of earliness and tardiness, cost, quality, and energy consumption. Then, an integrated multi-attribute decision-making method is introduced to select one solution that fits into the decision maker’s preference. NSGA-III is compared with three multi-objective evolutionary algorithms (MOEAs)-based scheduling methods, and the simulation results show that NSGA-III performs better in generating the Pareto solutions. In addition, the impacts of using different reference points and decoding methods are investigated.

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