Diversity and Equity Models

Sandoya, Fernando; Martı́nez-Gavara, Anna; Aceves, Ricardo; Duarte, Abraham; Martı́, Rafael

doi:10.1007/978-3-319-07124-4_61

Cited by 11 publications

(10 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Correlation between diversity measures can be seen in Table 3, obtained considering the result of the NSGA-II-based algorithm for a problem instance with |N | = 50 elements from which |M | = 5 had to be selected. This analysis coincides with the correlations presented by Sandoya in (3).…”

Section: Experiments 1: Objective Function Correlationsupporting

confidence: 91%

“…The cosine distance between two elements can be viewed as the angle between their attribute vectors, where a large angle between elements indicates a large degree of dissimilarity. It takes values in [-1, 1] reflecting the affinity between the individuals, as presented in (3).…”

Section: Distance Measure 2: Cosine Distancementioning

confidence: 99%

“…The growing interest in dealing with diversity in recent years has motivated efforts to study the management of equity, i.e., organizations are becoming increasingly interested in ensuring an equitable treatment of individuals or institutions (3). In fact the Operational Research area has studied several cases, which are summarized as follows:…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Maximum Diversity Problem. A Multi-Objective Approach

Escobar

Lopez-Pires

Barán

et al. 2018

CLEIej

Self Cite

View full text Add to dashboard Cite

The Maximum Diversity (MD) problem is the process of selecting a subset of elements where the diversity among selected elements is maximized. Several diversity measures were already studied in the literature, optimizing the problem considered in a pure mono-objective approach. This work presents for the first time multi-objective approaches for the MD problem, considering the simultaneous optimization of the following five diversity measures: (i) Max-Sum, (ii) Max-Min, (iii) Max-MinSum, (iv) Min-Diff and (v) Min-P-center. Two different optimization models are proposed: (i) Multi-Objective Maximum Diversity (MMD) model, where the number of elements to be selected is defined a-priori, and (ii) Multi-Objective Maximum Average Diversity (MMAD) model, where the number of elements to be selected is also a decision variable. To solve the formulated problems, a Multi-Objective Evolutionary Algorithm (MOEA) is presented. Experimental results demonstrate that the proposed MOEA found good quality solutions, i.e. between 98.85% and 100% of the optimal Pareto front when considering the hypervolume for comparison purposes.

show abstract

Section: Experiments 1: Objective Function Correlationsupporting

confidence: 91%

Section: Distance Measure 2: Cosine Distancementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Maximum Diversity Problem. A Multi-Objective Approach

Escobar

Lopez-Pires

Barán

et al. 2018

CLEIej

Self Cite

View full text Add to dashboard Cite

show abstract

“…There are many advantages, and also disadvantages, when using heuristic algorithm methods to solve optimization problems, as described [6] within the reasons to use heuristic methods which are as follows:…”

Section: Classic Heuristics To Solve Vrpmentioning

confidence: 99%

“…Metaheuristics that have been considered for this comparative study are shown below, which correspond to constructive and local search procedures [6].…”

Section: Metaheuristicsmentioning

confidence: 99%

Comparative Study of Algorithms Metaheuristics Based Applied to the Solution of the Capacitated Vehicle Routing Problem

Sandoya¹,

Lazo²,

Quiñónez³

2020

Novel Trends in the Traveling Salesman Problem

View full text Add to dashboard Cite

This chapter presents the best-known heuristics and metaheuristics that are applied to solve the capacitated vehicle routing problem (CVRP), which is the generalization of the TSP, in which the nodes are visited by more than one route. To find out which algorithm obtains better results, there are 30 test instances used, which are grouped into 3 sets of problems according to the position of the nodes. The study begins with an economic impact analysis of the transportation sector in companies, which represents up to 20% of the final cost of the product. This case study focuses on the CVRP for its acronym capacitated vehicle routing problem, analyzing the best-known heuristics such as Clarke & Wright and sweep, and the algorithms GRASP and simulated annealing metaheuristics based.

show abstract