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.
A novel optimization problem of carton box manufacturing industries is introduced in this paper. A mixed integer linear formulation with multiple objective functions is developed in order to determine the value of some criteria of carton raw sheets such as size, amount, and supplier under simultaneous minimization of multiple goals such as purchasing cost of raw sheets under discount policy, wastage remained from raw sheets, and quantity of surplus of carton boxes. In order to cope with the unstable market of this sector, some parameters of the proposed formulation such as demand value of the products and price given for raw sheets are assumed to be fuzzy numbers. To tackle such fuzzy multiobjective problem, first, the fuzzy problem is converted to a crisp form using the concepts of necessity‐based chance‐constrained modelling approach. Then a new hybrid form of the fuzzy programming approach is proposed to solve the obtained crisp multiobjective problem effectively. Computational experiments on a real case given by a carton box factory show the superior result of the proposed solution approach compared with the well‐known multiobjective solution methods taken from the literature.
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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