An efficient procedure for finding best compromise solutions to the multi-objective assignment problem

Belhoul, Lyes; Galand, Lucie; Vanderpooten, Daniel

doi:10.1016/j.cor.2014.03.016

Cited by 20 publications

(4 citation statements)

References 20 publications

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“…Multiobjective optimization is applied on large graphs and complex networks [57][58][59][60], for example, in the problems of splitting a social graph [61] or transport and logistics problems [62,63]. The structure of prefractal graphs makes it possible to parallelize wellknown sequential algorithms.…”

Section: Discussionmentioning

confidence: 99%

Introduction to the Class of Prefractal Graphs

Kochkarov

2022

Mathematics

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Fractals are already firmly rooted in modern science. Research continues on the fractal properties of objects in physics, chemistry, biology and many other scientific fields. Fractal graphs as a discrete representation are used to model and describe the structure of various objects and processes, both natural and artificial. The paper proposes an introduction to prefractal graphs. The main definitions and notation are proposed—the concept of a seed, the operations of processing a seed, the procedure for generating a prefractal graph. Canonical (typical) and non-canonical (special) types of prefractal graphs are considered separately. Important characteristics are proposed and described—the preservation of adjacency of edges for different ranks in the trajectory. The definition of subgraph-seeds of different ranks is given separately. Rules for weighting a prefractal graph by natural numbers and intervals are proposed. Separately, the definition of a fractal graph as infinite is given, and the differences between the concepts of fractal and prefractal graphs are described. At the end of the work, already published works of the authors are proposed, indicating the main backlogs, as well as a list of directions for new research. This work is the beginning of a cycle of works on the study of the properties and characteristics of fractal and prefractal graphs.

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Section: Discussionmentioning

confidence: 99%

Introduction to the Class of Prefractal Graphs

Kochkarov

2022

Mathematics

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“…Those are in the domain of feasible solutions, such that meeting one objective affects at least one other; that is, there are possible compromises between the objectives (Mohammed & Hordofa, 2016). Thus, the decision maker must use an appropriate method and select a more preferred and efficient solution, known as the best compromise solution (Belhoul et al, 2014).…”

Section: Gp and Modeling Process Quality Controlmentioning

confidence: 99%

A Goal Programming-Monte Carlo Simulation Methodology for Modeling Process Quality Control

Morán-Zabala,

Cogollo-Flórez

2023

Management and Production Engineering Review

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Quality profiling seeks to know the quality characteristics of products and processes to improve customer satisfaction and business competitiveness. It is required to develop new techniques and tools that upgrade and complement the traditional analysis of process variables. This article proposes a new methodology to model quality control of the process and product quality characteristics by applying optimization and simulation tools. The application in the production process of carbonated beverages allowed us to identify the most influential variables on the gas content and the degrees Brix of beverage.

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“…And, it is NP-hard since the min-max regret assignment problem, as a special case of the assignment problem, is known to be NP-hard [47]. As one of the most-studied, well-known, and important problems of discrete optimization, the assignment problem has been well studied, and many algorithms have been designed to solve it, including single-objective and multiobjective cases [48][49][50].…”

Section: Solution Algorithmmentioning

confidence: 99%

Prospect Theory-Based Two-Sided Satisfied and Stable Matching Mechanism for the Shared Parking Slots Problem

Xiao

Wang

2022

Journal of Advanced Transportation

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The contradiction between the dramatic increase in the aggregate number of automobiles and the short supply of parking spaces leads to parking difficulties. Sharing mode helps improve the efficiency of existing parking spaces, increase resource utilization, and alleviate the difficulty of parking. This paper focuses on the matching mechanism in the shared parking slots problem, which involves three agents: shared parking suppliers, shared parking demanders, and shared parking platform. We propose a prospect theory-based two-sided satisfied and stable matching model (PT-TSSM) with two objectives to maximize the satisfaction degree of both shared parking demanders and shared parking suppliers. Numerical experiments are illustrated to demonstrate the efficiency of the proposed model. Moreover, the PT-TSSM model is compared with the other two shared parking mechanisms. The proposed model considers the satisfaction degrees of both shared parking demanders and suppliers, while first book first serve (FBFS) cares only one side of the participants. And compared with deferred acceptance (DA), our model not only takes two-sided stable matching into account but also considers the satisfaction degree of all the demand and supply participants, which obtain a two-sided satisfied and stable matching scheme.

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An efficient procedure for finding best compromise solutions to the multi-objective assignment problem

Cited by 20 publications

References 20 publications

Introduction to the Class of Prefractal Graphs

Introduction to the Class of Prefractal Graphs

A Goal Programming-Monte Carlo Simulation Methodology for Modeling Process Quality Control

Prospect Theory-Based Two-Sided Satisfied and Stable Matching Mechanism for the Shared Parking Slots Problem

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