A mathematical programming model for a multi-objective supplier selection and order allocation problem with fuzzy objectives

A mixed integer programming model is proposed to solve supplier selection and order allocation problem for a manufacturer. In this model, quality, delivery performance, and purchasing cost are chosen as three criteria to select suppliers and set as objectives. Inventory level, goods flow balance, service level, supply ability, and marketing demand are considered as constraints. In the proposed model, the three objectives have different weights which are given by experts. However, the experts score the weight by many subjective factors. So, the fuzzy analytic hierarchy process (FAHP) based approach is used to calculate the weighted values. In the end, a case study illustrates the advantage of weighted values solved by FAHP. And the result shows that a weighted model is more advantageous for supplier selection and order allocation.

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A hybrid meta-heuristics approach for supplier selection and order allocation problem for supplying risks of recyclable raw materials

International Journal of Industrial Engineering Computations ◽

10.5267/j.ijiec.2020.12.001 ◽

2021 ◽

pp. 177-190 ◽

Cited By ~ 1

Author(s):

Nguyen Hoang Son ◽

Nguyen Van Hop

Keyword(s):

Supplier Selection ◽

Programming Model ◽

Raw Materials ◽

Real Life ◽

Optimal Solution ◽

Allocation Problem ◽

Mixed Integer ◽

Order Allocation ◽

Supply Risks ◽

The Right

In this work, a mixed-integer linear programming model is formulated to allocate the appropriate orders to the right suppliers for recyclable raw materials. We modify the previous model for the supplier selection and order allocation problem for stochastic demand to cope with the supply risks of recyclable raw materials such as insufficient supply quantity, defective rate, and late delivery. The optimal solution of the mathematical model is the benchmark for small-sized problems. Then, a hybrid meta-heuristic of Particles Swarm Optimization and Grey Wolf Optimization (PSO-GWO) is proposed to search for the best solution for large-sized problems. A real-life case study of a steel manufacturer with two factories in Vietnam is presented to validate the proposed approach. Some experiments have been tested to confirm the performance of the hybrid PSO-GWO approach.

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Multi-objective Based Fuzzy Mathematical Programming Model for Green Logistics Network Design Under Uncertainty

LISS 2014 ◽

10.1007/978-3-662-43871-8_202 ◽

2015 ◽

pp. 1399-1406

Author(s):

Bin Yang ◽

Weishan Sun ◽

Yong Li ◽

Zhihua Hu ◽

Jiankun Hu

Keyword(s):

Mathematical Programming ◽

Network Design ◽

Programming Model ◽

Design Under Uncertainty ◽

Fuzzy Mathematical Programming ◽

Mathematical Programming Model ◽

Green Logistics ◽

Logistics Network ◽

Multi Objective

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Optimal project portfolio selection with reinvestment strategy considering sustainability in an uncertain environment: a multi-objective optimization approach

Kybernetes ◽

10.1108/k-11-2020-0737 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Mohammadali Zarjou ◽

Mohammad Khalilzadeh

Keyword(s):

Mathematical Programming ◽

Portfolio Selection ◽

Programming Model ◽

Sustainability Indicators ◽

Selection Problem ◽

Project Portfolio ◽

Mathematical Programming Model ◽

Content Type ◽

Multi Objective ◽

Project Portfolio Selection

PurposeThis study aims to develop a model for project portfolio selection considering organizational goals such as budgets, sustainability cash flow and reinvestment strategy under an uncertain environment.Design/methodology/approachA multi-objective mathematical programming model is proposed for project selection, which takes the social, environmental and financial aspects into account as the objectives of the project portfolio selection problem. The project evaluation and selection process in one of the large capitals in the Middle East with numerous urban construction projects was considered as a real case study, in which the subjects of environmental and social sustainability are of great importance. Then, the most significant criteria for project evaluation and selection based on sustainability were identified and ranked using the fuzzy best-worst method (BWM).FindingsThe criterion of “defining clear and real objectives” was ranked first, “project investment return period” was ranked second, “minimum changes in the predicted range” was ranked third, and the other ten sustainability indicators were ranked as well. Next, the presented mathematical programming model was solved using the augmented e-constraint method. The sensitivity analysis indicated that increasing the amount of investments in projects would increase their net present value. Also, increased investment had no effect on sustainability, while decreased investment caused sustainability to not being optimal.Originality/valueThis study focuses on the impact of the amount of investments on projects, and the associated costs of sustainable projects. Further to the authors' knowledge, there has been no relevant study taking uncertainty into account. Also, very few studies proposed a mathematical programming model for the project portfolio selection problem. Moreover, this research uses the brainstorming and Delphi method to identify the sustainability indicators influencing the organization and screens the evaluation indicators. Furthermore, the weights of the evaluation indicators are determined using the fuzzy BWM based on the consistency of opinions.

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