1,720,976 research outputs found
Solving the Asymmetric Traveling Salesman Problem with Periodic Constraints
No full textIn this article we describe a heuristic algorithm to solve
the asymmetrical traveling salesman problem with periodic
constraints over a given m-day planning horizon.
Each city i must be visited ri times within this time horizon,
and these visit days are assigned to i by selecting
one of the feasible combinations of ri visit days with the
objective of minimizing the total distance traveled by the
salesman. The proposed algorithm is a heuristic that
starts by designing feasible tours, one for each day of
the m-day planning horizon, and then employs an improvement procedure that modifies the assigned combination to each of the cities, to improve the objective
function. Our heuristic has been tested on a set of test
problems purposely generated by slightly modifying
known test problems taken from the literature. Computational
comparisons on special instances indicate encouraging
results
An improved heuristic for the period traveling salesman problem
No full textWe propose a heuristic algorithm for the solution of the period traveling salesman problem. Computational results obtained on the classical test instances of the literature show that the total distance obtained by the algorithm is not worse than the best-known total distance in 95% of the instances and is strictly better in 18 of the 40 tested instances
Minimizing the total cost in an integrated Vendor-Managed Inventory System
No full textIn this paper we consider a complex production-distribution system, where a facility produces (or orders from an external supplier) several items which are distributed to a set of retailers by a fleet of vehicles. We consider Vendor-Managed Inventory (VMI) policies, in which the facility knows the inventory levels of the retailers and takes care of their replenishment policies. The production (or ordering) policy, the retailers replenishment policies and the transportation policy have to be determined so as to minimize the total system cost. The cost includes the fixed and variable production costs at the facility, the inventory costs at the facility and at the retailers and the transportation costs, that is the fixed costs of the vehicles and the traveling costs. We study two different types of VMI policies: The order-up-to level policy, in which the order-up-to level quantity is shipped to each retailer whenever served (i.e. the quantity delivered to each retailer is such that the maximum level of the inventory at the retailer is reached) and the fill-fill-dump policy, in which the order-up-to level quantity is shipped to all but the last retailer on each delivery route, while the quantity delivered to the last retailer is the minimum between the order-up-to level quantity and the residual transportation capacity of the vehicle. We propose two different decompositions of the problem and optimal or heuristic procedures for the solution of the subproblems. We show that, for reasonable initial values of the variables, the order in which the subproblems are solved does not influence the final solution. We will first solve the distribution subproblem and then the production subproblem. The computational results show that the fill-fill-dump policy reduces the average cost with respect to the order-up-to level policy and that one of the decompositions is more effective. Moreover, we compare the VMI policies with the more traditional Retailer-Managed Inventory (RMI) policy and show that the VMI policies significantly reduce the average cost with respect to the RMI policy
Optimization of an Integrated Production-Distribution System
No full textTechnical Report n. 287, Department of Quantitative Methods, University of Bresci
Analysis of the maximum level policy in a production-distribution system
No full textTechnical Report n. 325, Department of Quantitative Methods, University of Bresci
Deterministic order-up-to level strategies for the minimization of the logistic costs in distribution systems
No full text
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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