Time-dependent Vehicle Routing Problem is one of the most applicable but least-studied variants of routing and scheduling problems. In this paper, a novel mathematical formulation of time-dependent vehicle routing problems with heterogeneous fleet, hard time widows and multiple depots, is proposed. To deal with the traffic congestions, we also considered that the vehicles are not forced to come...

Research on semantics in Genetic Programming (GP) has increased dramatically over the last number of years. Results in this area clearly indicate that its use in GP can considerably increase GP performance. Motivated by these results, this paper investigates for the first time the use of Semantics in Muti-Objective GP within the well-known NSGA-II algorithm. To this end, we propose two forms of...

In this paper, a GPGPU (general purpose graphics processing unit) compatible Archived based Stochastic Ranking Evolutionary Algorithm (G-ASREA) is proposed, that ranks the population with respect to an archive of non-dominated solutions. It reduces the complexity of the deterministic ranking operator from O(mn) to O(man) and further speeds up ranking on GPU. Experiments compare G-ASREA with a C...

Obtaining a well distributed non-dominated Pareto front is one of the key issues in multi-objective optimization algorithms. This paper proposes a new variant for the elitist selection operator to the NSGA-II algorithm, which promotes well distributed non-dominated fronts. The basic idea is to replace the crowding distance method by a maximin technique. The proposed technique is deployed in wel...

An improved harmony search algorithm for constrained multi-objective optimization problems is proposed in this paper. Inspired by Particle Swarm Optimization, an inductor particle is introduced to speed up the convergence rate of the CMOHS. Two populations are adopted to increase the opportunity of finding the optimal solutions. Numerical experiments are divided into two parts: the first one co...

In this paper, we propose a novel approach based on NSGA-II to address the problem of optimizing the aggregation of three different basic similarity measures (syntactic measure, linguistic measure and taxonomy-based measure) and get a single similarity metric. Comparing with conventional genetic algorithm, the proposed method is able to realize three goals simultaneously, i.e., maximizing the a...

A kind of unrelated parallel machines scheduling problem is discussed. The memberships of fuzzy due dates denote the grades of satisfaction with respect to completion times with jobs. Objectives of scheduling are to maximize the minimum grade of satisfaction while makespan is minimized in the meantime. Two kind of genetic algorithms are employed to search optimal solution set of the problem. Bo...