2,464 research outputs found
On green routing and scheduling problem
The vehicle routing and scheduling problem has been studied with much
interest within the last four decades. In this paper, some of the existing
literature dealing with routing and scheduling problems with environmental
issues is reviewed, and a description is provided of the problems that have
been investigated and how they are treated using combinatorial optimization
tools
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Combinatorial optimization and metaheuristics
Today, combinatorial optimization is one of the youngest and most active areas of discrete mathematics. It is a branch of optimization in applied mathematics and computer science, related to operational research, algorithm theory and computational complexity theory. It sits at the intersection of several fields, including artificial intelligence, mathematics and software engineering. Its increasing interest arises for the fact that a large number of scientific and industrial problems can be formulated as abstract combinatorial optimization problems, through graphs and/or (integer) linear programs. Some of these problems have polynomial-time (“efficient”) algorithms, while most of them are NP-hard, i.e. it is not proved that they can be solved in polynomial-time. Mainly, it means that it is not possible to guarantee that an exact solution to the problem can be found and one has to settle for an approximate solution with known performance guarantees. Indeed, the goal of approximate methods is to find “quickly” (reasonable run-times), with “high” probability, provable “good” solutions (low error from the real optimal solution). In the last 20 years, a new kind of algorithm commonly called metaheuristics have emerged in this class, which basically try to combine heuristics in high level frameworks aimed at efficiently and effectively exploring the search space. This report briefly outlines the components, concepts, advantages and disadvantages of different metaheuristic approaches from a conceptual point of view, in order to analyze their similarities and differences. The two very significant forces of intensification and diversification, that mainly determine the behavior of a metaheuristic, will be pointed out. The report concludes by exploring the importance of hybridization and integration methods
On the use of reference points for the biobjective Inventory Routing Problem
The article presents a study on the biobjective inventory routing problem.
Contrary to most previous research, the problem is treated as a true
multi-objective optimization problem, with the goal of identifying
Pareto-optimal solutions. Due to the hardness of the problem at hand, a
reference point based optimization approach is presented and implemented into
an optimization and decision support system, which allows for the computation
of a true subset of the optimal outcomes. Experimental investigation involving
local search metaheuristics are conducted on benchmark data, and numerical
results are reported and analyzed
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