InterCriteria Analyzis of Hybrid Ant Colony Optimization Algorithm for Multiple Knapsack Problem

Fidanova, Stefka; Ganzha, Maria; Roeva, Olympia

doi:10.15439/2021f22

Cited by 3 publications

(3 citation statements)

References 34 publications

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“…The following properties hold: 1) From the definitions of the sets P 1 , Y 1 and Z 1 it follows: If Y 1 = ∅, then W n = P 1 ∪ Z 1 and P 1 is the set of Pareto optimal paths. This means that in (14) the constant k 0 = 1, and the calculations of the POP procedure will stop.…”

Section: Pareto Optimal Solutions Setmentioning

confidence: 99%

“…For example, in [13] the authors propose a so- Thematic track: Computational Optimization lution to the biobjective shortest path problem that is based on a genetic algorithm for which the authors report to find the Pareto optimal set in 77% of the instances. Also, the probabilistic technique ant colony optimization (ACO) and its modifications are adopted in the solution of various complex combinatorial problems (see for example [14]). Heuristic methods often are adopted in various practical problems, like electric vehicle shortest path problem [15].…”

Section: Introductionmentioning

confidence: 99%

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List Of Pareto Optimal Solutions of a Biobjective Shortest Path Problem

Laskov,

Marinov

2023

Annals of Computer Science and Information Systems

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Many applications in practice involve the search for a shortest path in a network by optimizing two conflicting objective functions. Such problems often are referred to as biobjective optimization problems. Their goal is to find special optimal paths that are nondominated and are also known in the specialized literature as to as Pareto optimal. While most of the existing methods aim to find the minimum complete set of Pareto optimal paths, we propose an approach that is able to generate a list of all Pareto optimal solutions in a given network.The described method solves the biobjective optimization problem in the case in which the first objective function is a linear (MINSUM), while the second objective function is from the "bottleneck" type (MAXMIN). The presented approach is based on two modifications of the Dijkstra's shortest path algorithm that solve the MINSUM and the MAXMIN problems respectively.We prove the correctness and the computational complexity of the presented algorithms. Also, we provide detailed numerical examples that illustrate their execution.

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Section: Pareto Optimal Solutions Setmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

List Of Pareto Optimal Solutions of a Biobjective Shortest Path Problem

Laskov,

Marinov

2023

Annals of Computer Science and Information Systems

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“…Step 5. After finding the most effective franchisee, we will optimize the evaluation system for the next procedures using the intercriteria method (ICrA, [7], [8], [14]).…”

Section: A An Optimal Temporal Intuitionistic Fuzzy Algorithm For Ass...mentioning

confidence: 99%

Software Implementation of the Optimal Temporal Intuitionistic Fuzzy Algorithm for Franchisee Selection

Traneva¹,

Mavrov²,

Tranev³

2022

Annals of Computer Science and Information Systems

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The selection of the most suitable franchisee applicant in an uncertain environment in a particular moment of time is a key decision for a franchisor and the success of a franchising business. In this work, for the first time, we describe a problem for choosing the optimal candidate for the franchise chain and algorithm for a solution in terms of temporal intuitionistic fuzzy pairs and index matrices as a means for data analysis in uncertain conditions over time. We also use our software utility to demonstrate the proposed algorithm and to apply the decision support approach to a franchisee selection for the largest fast food restaurant chain in Bulgaria.

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