Supplier selection and order allocation decisions under quantity discount and fast service options

Alegöz, Mehmet; Yapıcıoğlu, Haluk

doi:10.1016/j.spc.2019.02.006

Cited by 59 publications

(22 citation statements)

References 29 publications

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“… Wu et al (2019a) presented an MCDM based on IT2FAHP in order to optimize renewable energy projects from the perspective of sustainability. Alegoz and Yapicioglu (2019) proposed a MCDM method with IT2FAHP, using TOPSIS and goal programming for supplier selection. In addition to these articles, studies on unmanned aerial vehicles (UAV) have also been conducted ( Bravo-Mosquera et al, 2019 ; Bravo-Mosquera et al, 2017 ).…”

Section: Literature Reviewmentioning

confidence: 99%

Aircraft selection by applying AHP and TOPSIS in interval type-2 fuzzy sets

Kiracı

Akan

2020

Journal of Air Transport Management

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The selection of the appropriate aircraft can bring competitive advantages to airlines, however, there are a number of factors which introduce a degree of uncertainty to the selection process. By removing this uncertainty, airlines can increase their chances of achieving their long-term goals. New Multi-Criteria Decision Making (MCDM) methods provide decision-makers with a satisfactory solution for choosing suitable aircraft. Therefore, we focused on the multi-dimensional evaluation and selection of the most suitable commercial aircraft alternatives by using new MCDM method. This article provides decision support to airline planners on the selection of commercial aircraft under uncertainty. In the study, unlike other studies in the literature on aircraft selection, the model presented here uses an Interval Type-2 Fuzzy Analytical Hierarch Process (IT2FAHP) and Interval Type-2 Fuzzy Technique for Order Preference by Similarity to an Ideal Solution (IT2FTOPSIS) hybrid methods. The proposed model for aircraft selection allows commercial airlines to evaluate the aircraft in terms of specific criteria: economic performance, technical performance, and environmental impact, and, as a result, it helps decision makers select appropriate aircraft in an uncertain environment. In addition to use by commercial airlines, the methods in the study can also be applied to the selection of training aircraft, cargo aircraft and military aircraft. Our findings show that the Airbus A321neo is the most suitable commercial aircraft in terms of technical aspects, economic aspects and environmental aspects for airlines.

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Section: Literature Reviewmentioning

confidence: 99%

Aircraft selection by applying AHP and TOPSIS in interval type-2 fuzzy sets

Kiracı

Akan

2020

Journal of Air Transport Management

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“…Offering quantity discount is an important feature in the selection of the best suppliers. Therefore, each company can achieve low cost while allocating large volume orders to the suppliers (Alegoz and Yapicioglu 2019 ).…”

Section: Introductionmentioning

confidence: 99%

Supplier selection and order allocation: a literature review

Naqvi

Amin

2021

J. of Data, Inf. and Manag.

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The goals of procurement managers in every industry usually are acquiring the right materials at the right time, at the right prices and quantities. To achieve these goals, the best suppliers should be selected. Supplier selection and order allocation have been studied extensively in the past. In this paper, we review the peer-reviewed journal publications in this area. The taxonomy in this research includes problem domain and operations research techniques. The problem domain is examined in three subcategories including Literature Reviews (LR), Deterministic Optimization (DO) models, and Uncertain Optimization (UO) models. Then, observations, recommendations, and future research directions in the field of supplier selection and order allocation are discussed.

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“…Duan and Ventura [12] formulated a multiperiod mixed-integer linear programming (MILP) model with single product and multisupplier; meanwhile, lead time and order frequency are took into account in the model. Alegoz and Yapicioglu [13] used TOPSIS and AHP to determine the weights of different objectives.…”

Section: Order Allocationmentioning

confidence: 99%

Multiobjective Sustainable Order Allocation Problem Optimization with Improved Genetic Algorithm Using Priority Encoding

Fan

Gao

2019

Mathematical Problems in Engineering

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Recently, incorporating carbon emissions into order allocation decisions has attracted considerable attention among scholars and industrialists. Moreover, affected by the random fluctuations of the man, machine, material, method, and environment (4M1E), the production process is usually imperfect with defective products. Reducing product defective rates can effectively improve the quality of the order allocation process. Therefore, considering product defective rate and carbon emission, a multiobjective integer nonlinear programming (INLP) formulation is presented to address this multiproduct, multiperiod, and multi-OEM order allocation problem. Furthermore, exploring the existing literatures, an improved genetic algorithm using priority encoding (IGAUPE) is put forward as a novel optimization technique. Finally, numerical experiments are conducted to validate the correctness of the proposed INLP model as well as the effectiveness of the proposed algorithm. Compared with the genetic algorithm using binary encoding (GAUBE), genetic algorithm using two-layer encoding (GAUTE), and LINGO software, the experiment results show that IGAUPE can improve the efficiency and effectiveness within the predetermined time limit when solving large-scale instances.

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Supplier selection and order allocation decisions under quantity discount and fast service options

Cited by 59 publications

References 29 publications

Aircraft selection by applying AHP and TOPSIS in interval type-2 fuzzy sets

Aircraft selection by applying AHP and TOPSIS in interval type-2 fuzzy sets

Supplier selection and order allocation: a literature review

Multiobjective Sustainable Order Allocation Problem Optimization with Improved Genetic Algorithm Using Priority Encoding

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