A study of a robust multi-objective supplier-material selection problem

Niroomand, Sadegh; Mosallaeipour, Sam; Mahmoodirad, Ali; Vízvári, Béla

doi:10.1093/imaman/dpy001

Cited by 5 publications

(4 citation statements)

References 16 publications

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“…In this validity study, the following issues are considered. The global criterion approach (see 53 ) is used to overcome the multi‐objectivity of the model. Some inputs of the model in this instance are as follows,Two suppliers are considered. Two potential plants, two potential DCs, and five customers are considered where one of them is dummy. Two types of transportation devices between suppliers and plants, two types of transportation devices between plants and DCs, and two types of transportation devices between plants/DCs and customers are considered. Three types of products, two types of raw materials, and two different technologies are considered. The instance is solved optimally in 10 seconds and the following objective function values are obtained,Objective function 1: 1,696,662.00, Objective function 2: 299,142.00, Objective function 3: 876.95. …”

Section: Problem Description and Formulationmentioning

confidence: 99%

“…In order to compare the results of the proposed meta‐heuristic approaches with exact solution methods, the global criterion approach (see Reference 53) is used to convert the multi‐objective problem in Section 2 to a single objective form. Then the test problems in Table 2 are solved by CPLEX solver of GAMS where 15,000 seconds CPU running time is allowed.…”

Section: Computational Studymentioning

confidence: 99%

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Multi‐objective location‐allocation‐routing problem of perishable multi‐product supply chain with direct shipment and open routing possibilities under sustainability

Fishani

Mahmoodirad

Niroomand

et al. 2022

Concurrency and Computation

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In this study a multi-objective formulation is proposed for designing a supply chain of perishable products including suppliers, plants, distributors, and customers under sustainable development. In addition to the studies of the literature, direct shipment between producers and customers and also alternative products possibility are allowed. In this problem the objectives like facilities establishment costs, transportation costs, negative environmental impacts, and social impact (fixed and variable employment rates) are optimized simultaneously. As in real situations, most of the transportation activities of such supply chain are performed by hiring transportation devices, the open routing logic is applied to form the travelling path of each hired transportation device. Furthermore, the possibility of direct shipment from the plants to the customers is considered in order to increase profitability of the plants. Because of the NP-hard nature of the supply chain design problems, some meta-heuristic solution approaches of the literature are modified to multi-objective form and applied to solve the problem. Several test problems from small to large sizes are generated randomly to evaluate the meta-heuristic algorithms. As a result, among the proposed algorithms, the multi-objective grey wolf optimizer (MGWO) perform better than others by considering four wellknown evaluation metrics. At the end, a case study from perishable products supply chain of Iran is solved and analyzed to show the applicability of the proposed problem.

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Section: Problem Description and Formulationmentioning

confidence: 99%

Section: Computational Studymentioning

confidence: 99%

Multi‐objective location‐allocation‐routing problem of perishable multi‐product supply chain with direct shipment and open routing possibilities under sustainability

Fishani

Mahmoodirad

Niroomand

et al. 2022

Concurrency and Computation

Self Cite

View full text Add to dashboard Cite

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“…Unfortunately, interpreting the membership functions and utilizing them for solving a problem is not an easy task [9]. Researchers have proposed several ways of providing an adequate solution to the problems that deal with the uncertain parameters [30]. One of the best methods for dealing with this category of problems is the "uncertainty theory" introduced by [31] and [32], which has attracted lots of attention recently [33]- [35].…”

Section: Accepted Manuscriptmentioning

confidence: 99%

A congested capacitated multi-level fuzzy facility location problem: An efficient drone delivery system

Shavarani

Mosallaeipour

Golabi³

et al. 2019

Computers & Operations Research

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Online retailers invest an enormous amount of funds in delivering products to customers. In recent years, these delivery costs have increased as a result of changes in fuel costs, which has brought new challenges to retailers in terms of offering competitive prices. Many retailers have begun to utilize a drone-based aerial delivery system as an alternative solution to overcome the problems related to the high transportation costs and traffic jams in large cities. This study provides a mathematical model for minimizing the total costs of the aerial delivery system concerned with refuel stations, warehouses, drone procurement, and transportation. The waiting time of the customers is restricted based on the M/G/K queueing system. The fuel stations and warehouses are the main components of the network. The demand (occurring at the lowest level) is ultimately satisfied via launch stations (the network's highest level). Refuel stations support drones along their long routes between the launch stations and demand points. To account for the different levels of the facilities, a multi-level facility location approach is utilized. Moreover, the nondeterministic nature of the problem is tackled using fuzzy variables. The ultimate mathematical model is a congested fuzzy capacitated multi-level facility location problem that is solved by the possibilistic approach.

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“…Consequently, the EDSSs are much more useful tools when they are uncertainty-proof (robust) by both incorporating the uncertainty of the parameters into the PROM and using an effective method to deal with them when offering a solution. To the best of author's knowledge, there is no evidence of a prior study on the application of the robust EDSS in the realm of FREM (Ghadiri Nejad et al, 2018;Golabi et al, 2017;Mosallaeipour, 2017;Niroomand et al, 2018;Shavarani et al, 2017;Mardani et al, 2015).…”

Section: Jcre 221mentioning

confidence: 99%

A robust expert decision support system for making real estate location decisions, a case of investor-developer-user organization in industry 4.0 era

Mosallaeipour

Shavarani

Steens

et al. 2019

JCRE

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Purpose This paper aims to introduce a practical expert decision support system (EDSS) for performing location analysis and making real estate location decisions in the organization’s facility and real estate management (FREM) department in presence of several decision criteria, under risk and uncertainty. This tool is particularly useful for making strategic decisions in facility planning, portfolio management, investment appraisal, development project evaluations and deciding on usage possibilities in an unbiased, objective manner. Design/methodology/approach The proposed EDSS uses fuzzy logic and uncertainty theory as two of the most useful tools to deal with uncertainties involved in the problem environment. The system performs an unbiased mathematical analysis on the input data provided by the decision-maker, using a combination of Analytical Hierarchy Process (AHP) and Global Criterion Method; determines a suitable compromise level between the objectives; and delivers a set of locations that complies best with the outlined desires of the management as the final solution. The application of the system is tested on a real case and has delivered satisfactory results. Findings The proposed EDSS took the defined objectives, the list of alternative locations, and their attributes as the required input for problem-solving, and used a combination of AHP, Possibilistic approach, and global criterion method to solve the problem. The delivered outcome was a set of proper locations with the right attributes to meet all objectives of the organization at a satisfactory level, confirmed by the problem owners. Originality/value The application of such a system with such a degree of preciseness and complexity has been very limited in the literature. The system designed in this study is an Industry 4.0 decision making tool. For designing this system several body of knowledge are used. The present study is particularly useful for making strategic decisions in the domains of portfolio management, investment appraisal, project development evaluations and deciding on property usage possibilities. The proposed EDSS takes the information provided by the experts in the field (through qualitative and quantitative data collecting) as the inputs and operates as an objective decision-making tool using several bodies of knowledge considering the trends and developments in the world of FREM. The strong scientific method used in the core of the proposed EDSS guarantees a highly accurate result.

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A study of a robust multi-objective supplier-material selection problem

Cited by 5 publications

References 16 publications

Multi‐objective location‐allocation‐routing problem of perishable multi‐product supply chain with direct shipment and open routing possibilities under sustainability

Multi‐objective location‐allocation‐routing problem of perishable multi‐product supply chain with direct shipment and open routing possibilities under sustainability

A congested capacitated multi-level fuzzy facility location problem: An efficient drone delivery system

A robust expert decision support system for making real estate location decisions, a case of investor-developer-user organization in industry 4.0 era

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