A Multi-Objective ACO to Solve the Daily Carpool Problem

Abstract

In urban areas, the cost of road congestion has paid great attention to the sociological, technological and environmental aspects, such as the optimal route and fuel consumption. This step is towards a smarter vehicle mobility where the travel time will be planned and dynamically adapted to changes with actual status of the traffic flow. In this article a multi-objective ACO algorithm is proposed to solve the daily carpooling problem. In particular, a set of decision variables are proposed in order to minimize three objective functions subject to a set of constraints on these objectives.

Environmental and social implications of incorporating carpooling service on a customized bus system

“…ACO procedure is a widely used meta-heuristic to solve the combinatorial optimization problems concerning more than one objective (Sahraoui et al, 2018). However, early adaptations of multiobjective ACO applied equal or fixed weights for heuristic and/or pheromone trails in each objective, and then aggregated them based on a weighted sum or weighted product approach (Lopez-Ibanez and Stutzle, 2012).…”

Optimal Test Case Selection Using Ant Colony and Rough Sets

“…Antcolonyoptimization,whichisametaheuristicmethod,iswidelyusedforfindingapproximate solutionsforvarioussearchoptimizationproblems (Sonia,2016;Maryam,2016;Yietal.,2017;Sahraoui et al, 2018) namely, multi-criteria test case selection and classification problems. The filteredtestcasesobtainedarefurtheroptimizedusingantcolonyoptimizationapproach (Kumaret al,2014b).Inthisapproachthefitnessofthesubsetoftestcasesselectedareevaluatedusingthe executiontimeofthetestcases.ThefirstACOalgorithm,antsystem(AS),wasdevelopedbyDorigo etal.…”