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Heuristic Solution (heuristic + solution)

Distribution by Scientific Domains
Business, Economics, Finance and Accounting71%
Mathematics and Statistics28%

Selected Abstracts

Coordinated Capacitated Lot-Sizing Problem with Dynamic Demand: A Lagrangian Heuristic

DECISION SCIENCES, Issue 1 2004
E. Powell Robinson Jr.
ABSTRACT Coordinated replenishment problems are common in manufacturing and distribution when a family of items shares a common production line, supplier, or a mode of transportation. In these situations the coordination of shared, and often limited, resources across items is economically attractive. This paper describes a mixed-integer programming formulation and Lagrangian relaxation solution procedure for the single-family coordinated capacitated lot-sizing problem with dynamic demand. The problem extends both the multi-item capacitated dynamic demand lot-sizing problem and the uncapacitated coordinated dynamic demand lot-sizing problem. We provide the results of computational experiments investigating the mathematical properties of the formulation and the performance of the Lagrangian procedures. The results indicate the superiority of the dual-based heuristic over linear programming-based approaches to the problem. The quality of the Lagrangian heuristic solution improved in most instances with increases in problem size. Heuristic solutions averaged 2.52% above optimal. The procedures were applied to an industry test problem yielding a 22.5% reduction in total costs. [source]

Hierarchical multiobjective routing in Multiprotocol Label Switching networks with two service classes: a heuristic solution

INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH, Issue 3 2009
Rita Girão-Silva
Abstract Modern multiservice network routing functionalities have to deal with multiple, heterogeneous and multifaceted Quality of Service (QoS) requirements. A heuristic approach devised to find "good" solutions to a hierarchical multiobjective alternative routing optimization problem in Multiprotocol Label Switching networks with two service classes (and different types of traffic flows in each class), namely QoS and Best Effort services, formulated within a hierarchical network-wide optimization framework, is presented. This heuristic solution is based on a bi-objective constrained shortest path model and is applied to a test network used in a benchmarking case study. An experimental study based on analytic and discrete event simulation results is presented, allowing for an assessment of the quality of results obtained with this new heuristic solution for various traffic matrices. A dynamic version of the routing method is formulated and its performance with the same case study network is analysed. [source]

Algorithms for the multi-item multi-vehicles dynamic lot sizing problem

NAVAL RESEARCH LOGISTICS: AN INTERNATIONAL JOURNAL, Issue 2 2006
Shoshana Anily
Abstract We consider a two-stage supply chain, in which multi-items are shipped from a manufacturing facility or a central warehouse to a downstream retailer that faces deterministic external demand for each of the items over a finite planning horizon. The items are shipped through identical capacitated vehicles, each incurring a fixed cost per trip. In addition, there exist item-dependent variable shipping costs and inventory holding costs at the retailer for items stored at the end of the period; these costs are constant over time. The sum of all costs must be minimized while satisfying the external demand without backlogging. In this paper we develop a search algorithm to solve the problem optimally. Our search algorithm, although exponential in the worst case, is very efficient empirically due to new properties of the optimal solution that we found, which allow us to restrict the number of solutions examined. Second, we perform a computational study that compares the empirical running time of our search methods to other available exact solution methods to the problem. Finally, we characterize the conditions under which each of the solution methods is likely to be faster than the others and suggest efficient heuristic solutions that we recommend using when the problem is large in all dimensions. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2006. [source]

New approaches for solving the block-to-train assignment problem

NETWORKS: AN INTERNATIONAL JOURNAL, Issue 1 2008
Krishna C. Jha
Abstract Railroad planning involves solving two optimization problems: (i) the blocking problem, which determines what blocks to make and how to route traffic over these blocks; and (ii) the train schedule design problem, which determines train origins, destinations, and routes. Once the blocking plan and train schedule have been obtained, the next step is to determine which trains should carry which blocks. This problem, known as the block-to-train assignment problem, is considered in this paper. We provide two formulations for this problem: an arc-based formulation and a path-based formulation. The latter is generally smaller than the former, and it can better handle practical constraints. We also propose exact and heuristic algorithms based on the path-based formulation. Our exact algorithm solves an integer programming formulation with CPLEX using both a priori generation and dynamic generation of paths. Our heuristic algorithms include a Lagrangian relaxation-based method as well as a greedy construction method. We present computational results of our algorithms using the data provided by a major US railroad. We show that we can obtain an optimal solution of the block-to-train assignment problem within a few minutes of computational time, and can obtain heuristic solutions with 1,2% deviations from the optimal solutions within a few seconds. © 2007 Wiley Periodicals, Inc. NETWORKS, 2008 [source]