Engineering design problems are often multi-objective in nature, which means trade-offs are
required between conflicting objectives. In this study, we examine the multi-objective …

Greedy randomized adaptive search procedures, or GRASP, were introduced by T. Feo and
M. Resende in 1989 as a probabilistic heuristic for solving hard set covering problems. Soon …

Metaheuristics are algorithms that have proven their efficiency on multi-objective
combinatorial optimisation problems. They often use local search techniques, either at their …

Multiobjective orienteering problems (MO-OPs) are classical multiobjective routing problems
and have received much attention in recent decades. This study seeks to solve MO-OPs …

Abstract Greedy Randomised Adaptive Search Procedure (GRASP) is one of the best-
known metaheuristics to solve complex combinatorial optimisation problems (COPs). This …

In this paper, we address an optimization problem resulting from the combination of the well-
known travelling salesman and knapsack problems. In particular, we target the orienteering …

The tourist trip design problem (TTDP) helps the trip planners, such as tourists, tour
companies, and government agencies, automate their trip planning. TTDP solver chooses …

In the last few years, the application of decision making to logistic problems has become
crucial for public and private organizations. Efficient decisions clearly contribute to improve …

This paper addresses the problem of finding multiple near-optimal, spatially-dissimilar paths
that can be considered as alternatives in the decision making process, for finding optimal …

Purpose The purpose of this research is to study the Multi-Skill Resource-Constrained Multi-
Project Scheduling Problem (MSRCMPSP), where (1) durations of activities depend on the …