Management Science
Transportation investment project selection using fuzzy multiobjective programming
Fuzzy Sets and Systems
Transportation projects selection process using fuzzy sets theory
Fuzzy Sets and Systems - special issue on fuzzy sets in traffic and transport systems
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Two-phases Method and Branch and Bound Procedures to Solve the Bi–objective Knapsack Problem
Journal of Global Optimization
Genetic Algorithms for the 0/1 Knapsack Problem
ISMIS '94 Proceedings of the 8th International Symposium on Methodologies for Intelligent Systems
ISDA '06 Proceedings of the Sixth International Conference on Intelligent Systems Design and Applications - Volume 02
A Hybrid Fine-Tuned Multi-Objective Memetic Algorithm
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Implementation of Simple Multiobjective Memetic Algorithms and Its Application to Knapsack Problems
International Journal of Hybrid Intelligent Systems
Muiltiobjective optimization using nondominated sorting in genetic algorithms
Evolutionary Computation
Multiobjective evolutionary algorithms: a comparative case studyand the strength Pareto approach
IEEE Transactions on Evolutionary Computation
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Evolutionary Computation
A combined approach for equipment selection: F-PROMETHEE method and zero-one goal programming
Expert Systems with Applications: An International Journal
A fuzzy assessment framework to select among transportation investment projects in Turkey
Expert Systems with Applications: An International Journal
A hybrid fuzzy rule-based multi-criteria framework for sustainable project portfolio selection
Information Sciences: an International Journal
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When evaluating transportation infrastructure projects and determining which of them will be carried out from a set of projects and given a budget constraint, several criteria need to be considered in the decision. Standard evaluation practices imply the aggregation of impacts into one utility function which is later optimized. Nevertheless these techniques used for translation of different measuring units into monetary terms are highly controversial. Multicriteria techniques can explicitly deal with different measuring units, however, they are not suitable to model interdependence relationships of projects that share a common characteristic (same route, location or target population, for instance). In this research we model this transportation planning problem, the multi-objective transportation infrastructure project selection problem (MTIPSP), as a constrained multi-objective optimization problem with quadratic objective functions, using a variation of the multi-objective 0-1 knapsack problem plus some additional constraints. Given the combinatorial nature of the problem, an evolutionary-based framework is used for the identification of Pareto solutions, and later, those with non-attractive properties are filtered using a Knee Identification Procedure. The final selection of the projects portfolio is made using a well known multicriteria decision aid method and including the decision makers' preferences based on the existing context.