Daniela Favaretto

Dynamic routing-and-inventory problems: a review

The paper presents a review of the available literature on a class of problems denoted as dynamic routing-and-inventory (DRAl) problems. They are characterized by the simultaneous relevance of routing and of inventory issues in a dynamic environment, within the framework of distribution logistics. A classification scheme is first proposed for these problems. Then the results obtained in this area are summarized. Finally, the papers available in the literature are clustered and discussed according to the proposed scheme.

A comparison of different solution approaches to the vehicle scheduling problem in a practical case

Abstract The Vehicle Scheduling Problem (VSP) consists in assigning a set of scheduled trips to a set of vehicles, satisfying a set of constraints and optimizing an objective function. A wide literature exists for the VSP, but usually not all the practical requirements of the real cases are taken into account. In the present paper a practical case is studied, and for it a traditional method is tailored and two innovative heuristics are developed. As the problem presents a multicriteria nature, each of the three algorithms adopts a different approach to multicriteria optimization. Scalarization of the different criteria is performed by the traditional algorithm. A lexicographic approach is followed by an algorithm based on logic programming. Finally, a Pareto optimization approach is implemented by a modified genetic algorithm. All the algorithms are tested on the real problem, and two of them produce interesting practical results. Scope and purpose This paper presents the practical experience with a real case of Vehicle Scheduling Problem (VSP). The VSP is a classical optimization problem which is faced in the operational planning of public transportation systems (see for instance Dantzig and Fulkerson. Naval Research Logistics Quarterly 1954;1:217–222). It consists in assigning a set of scheduled trips to a set of available vehicles, in such a way that each trip is associated to one vehicle and a cost function is minimized. For some versions of it, such as when all vehicles are equal and share the same depot, efficient algorithms exist (see for instance Bodin et al. Computers & Operations Research 1983;10:63–212, Carraresi and Gallo. European Journal of Operational Research 1984;16:139–151); nevertheless, real-life applications often turn out to be complex, due to the particular requirements which are present in practical situations, but are hard to be modeled. Practical requirements for this problem, usually not considered in the literature, include considering several criteria, producing different alternative solutions, and getting hints on how data could be modified to improve the effectiveness of the solutions. The paper analyzes the features of the real problem and discusses different algorithmic approaches for it. It has basically two purposes. The first is to analyze, formalize and comply with the experienced requirements of the practical problem. The second consists in assessing the applicability and performance of non-conventional heuristics and of a traditional exact method.

Ant colony system for a VRP with multiple time windows and multiple visits

Abstract The Vehicle routing problem with time windows is frequently found in literature, while multiple time windows are not often considered. In this paper a mathematical formulation of the vehicle routing problem with multiple time windows is presented, taking into account periodic constraints. An algorithm based on Ant Colony System is proposed and implemented. Computational results related to a purpose-built benchmark are finally reported.

On MAX - MIN ant system's parameters

The impact of the values of the most meaningful parameters on the behavior of

An ant colony system approach for variants of the traveling salesman problem with time windows

\cal M\!AX\!

Multiple Ant Colony Optimization for a Rich Vehicle Routing Problem: A Case Study

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Optimal control of advertising and production of a seasonal product with nondifferentiable demand

\cal MI\!N\!

On the Explorative Behavior of MAX---MIN Ant System

Ant System is analyzed. Namely, we take into account the number of ants, the evaporation rate of the pheromone, and the exponent values of the pheromone trail and of the heuristic measure in the random proportional rule. We propose an analytic approach to examining their impact on the speed of convergence of the algorithm. Some computational experiments are reported to show the practical relevance of the theoretical results.

Discrete frequency models for inventory management - an introduction

The Traveling Salesman Problem with Time Windows has important applications in routing and scheduling and has been extensively studied in literature. In the paper, a mathematical formulation of the temporal–Traveling Salesman Problem with Time Windows is presented and a meta-heuristic based on Ant Colony System is proposed and implemented. Computational experience on a benchmark problem is reported and a case study is analyzed, where interesting results are obtained.

A multiperiod production and advertising problemfor a seasonal product

Starting from a case study, a rich vehicle routing problem is analyzed. It is characterized by multiple time windows, heterogeneous fleet, maximum duration, and multiple visits. Two variants of Ant Colony Optimization are proposed in a multiple colonies framework. Two algorithms are tested, giving results that appear satisfactory with respect to the ones achieved by the firm.