On Neighborhood Tree Search

We consider the neighborhood tree induced by alternating the use of different neighborhood structures within a local search descent. We investigate the issue of designing a search strategy operating at the neighborhood tree level by exploring different paths of the tree in a heuristic way. We show that allowing the search to 'backtrack' to a previously visited solution and resuming the iterative variable neighborhood descent by 'pruning' the already explored neighborhood branches leads to the design of effective and efficient search heuristics. We describe this idea by discussing its basic design components within a generic algorithmic scheme and we propose some simple and intuitive strategies to guide the search when traversing the neighborhood tree. We conduct a thorough experimental analysis of this approach by considering two different problem domains, namely, the Total Weighted Tardiness Problem (SMTWTP), and the more sophisticated Location Routing Problem (LRP). We show that independently of the considered domain, the approach is highly competitive. In particular, we show that using different branching and backtracking strategies when exploring the neighborhood tree allows us to achieve different trade-offs in terms of solution quality and computing cost.Comment: Genetic and Evolutionary Computation Conference (GECCO'12) (2012

A new formulation approach for location routing problems

Cataloged from PDF version of article.A Location-Routing Problem (LRP) combines two difficult problems, facility location and vehicle routing, and as such it is inherently hard to solve. In this paper, we propose a different formulation approach than the common arc-based product-flow (Arc-BPF) approach in the literature. We associate product amounts to the nodes of the network resulting in a node-based product-flow (Node-BPF) formulation. Our main objective is to develop LRP models with fewer constraints and variables, which can be solved more efficiently. To introduce the proposed approach, we reformulate a complex four-index Arc-BPF LRP model from the literature as a three-index Node-BPF model, which computationally outperforms the former. We then introduce a heuristic method

Facility Location Problem of Beverage Distribution Considering Time Window and Land Use Plan Using GIS

As the boundaries and population of urban areas expand, beverage distributors may seek to expand the capacity in their distribution centers. As a result, they may need to add new locations or increase the utilization of their existing center. This paper investigates the facility location problem through network space, considering traversable truck roads, thereby providing a strategic decision for identifying a depot location in consideration of vehicle routings from a real application. For the analysis, a geospatial tool, which is embedded in the commercial software ArcMap®, was used for routing and calibrating the model. Ten candidates from commercial and industrial zones in the cities of Fargo, West Fargo, and Moorhead were considered for future distribution centers. The candidate locations were analyzed to determine which site minimizes the total transportation costs and travel miles in consideration of time window, vehicle capacity, heterogeneous vehicle types, land use plan, and hours-of-service. Most attractive candidates are close to the intersections of major highways. From the analysis, the study recommends locating a distribution center at three alternatives based on the average ranking method. This study can be used by distributors as they consider new locations and extra depots to support strategic planning to deal with mid-term and long-term growth of demand in beverage markets. This study provides a ready-to-use example of how to adopt state-of-the-art spatial technology and operations research using Geographic Information Systems (GIS), and bring it to state-of-practice

RANCANGAN LOKASI GUDANG ANTARA DENGAN MEMPERTIMBANGKAN RUTE TERPENDEK MENGGUNAKAN PENDEKATAN CAPACITATED LOCATION ROUTING PROBLEM (CLRP) UNTUK MEMINIMASI BIAYA DISTRIBUSI PADA PT. XYZ (STUDI KASUS : PT. XYZ KOTA BANDUNG)

PT. XYZ merupakan perusahaan yang bergerak di bidang usaha perdagangan barang/ritel di Kota Bandung. Permasalahan yang dialami perusahaan yaitu terdapat satu buah gudang utama yang harus melayani permintaan dari 68 ritel dengan masing-masing ritel menggunakan satu buah kendaraan berjenis colt diesel dengan kapasitas kendaraan 3 ton. Sehingga perusahaan perlu mengeluarkan biaya yang besar untuk dapat melayani seluruh permintaan dari ritel tersebut, untuk itu perlu dilakukan evaluasi penentuan lokasi gudang antara serta rute yang dilaluinya agar diperoleh rute baru dengan total biaya minimum. Alat yang digunakan agar mendapatkan lokasi depot antara beserta rutenya yaitu dengan pendekatan Location Routing Problem (LRP). Metode yang digunakan untuk pertama-tama yaitu Fuzzy C-means untuk menentukan cluster, dan untuk memperoleh lokasi gudang antara beserta rute yang dilaluinya yaitu Insertion Heuristic. Hasil dari analisis menggunakan Fuzzy C-Means yaitu terdapat 10 cluster dengan total demand tidak melebihi kapasitas kendaraan usulan yaitu kendaraan dengan kapasitas 6 ton. Hasil dari analisis penentuan lokasi gudang antara dan rute yang dilalui masing-masing cluster menggunakan metode insertion heuristic bahwa lokasi gudang antara melekat atau bersamaan dengan lokasi ritel yang memiliki total jarak terpendek. Total biaya yang didapatkan dari hasil perbaikan lokasi gudang beserta rute yang dilalui jika dibandingkan dengan kondisi eksisting menghasilkan pengurangan biaya sebesar Rp. 27.721.790 atau perusahaan dapat menghemat biaya sebesar 61,47%. Dari hasil tersebut dapat dipertimbangkan oleh perusahaan untuk dibuat lokasi gudang antara sesuai dengan hasil evaluasi menggunakan pendekatan Location Routing Problem (LRP). Kata Kunci : Location Routing Problem, Fuzzy C-Means, Insertion Heuristik, Lokasi Depot Antar

Cooperative game-theoretic features of cost sharing in location-routing

This article studies several variants of the location-routing problem using a cooperative game-theoretic framework. The authors derive characteristics in terms of subadditivity, convexity, and non-emptiness of the core. Moreover, for some of the game variants, it is shown that for facility opening costs substantially larger than the costs associated with routing, the core is always non-empty. The theoretical results are supported by numerical experiments aimed at illustrating the properties and deriving insights. Among others, it is observed that, while in general it is not possible to guarantee core allocations, in a huge majority of cases the core is non-empty

Modelación En Programación Matemática Y Resolución Del Problema De Localización-Ruteo En Logística Urbana

The implementation of urban distribution centers near to city centers to allow freight consolidation is a widely extended initiative worldwide, seeking to improve traffic congestion and quality of life in downtown, among others. This paper considers the problem of locating urban distribution centers and proposes an exact method, based on integer linear programming for strategic, tactical and operational decision-making. The aim is to solve, in an integer manner, location, sizing and operation (vehicle routing) problems in these logistics platforms. The model is validated using real-data taken from the city of SaintÉtienne, France. Computational experiments are also carried out in order to compare the proposed model with existing procedures from the literature. Results show the efficiency and effectiveness of the proposed model and its applicability in real decision-making for medium sized data sets

The location routing problem with facility sizing decisions

The location routing problem (LRP) integrates operational decisions on vehicle routing operations with strategic decisions on the location of the facilities or depots from which the distribution will take place. In other words, it combines the well-known vehicle routing problem (VRP) with the facility location problem (FLP). Hence, the LRP is an NP-hard combinatorial optimization problem, which justifies the use of metaheuristic approaches whenever large-scale instances need to be solved. In this paper, we explore a realistic version of the LRP in which facilities of different capacities are considered, i.e., the manager has to consider not only the location but also the size of the facilities to open. In order to tackle this optimization problem, three mixed-integer linear formulations are proposed and compared. As expected, they have been proved to be cost- and time- inefficient. Hence, a biased-randomized iterated local search algorithm is proposed. Classical instances for the LRP with homogeneous facilities are naturally extended to test the performance of our approach.Peer ReviewedPostprint (published version

An Adaptive Tabu Search Heuristic for the Location Routing Pickup and Delivery Problem with Time Windows with a Theater Distribution Application

The time constrained pickup and delivery problem (PDPTW) is a problem of finding a set of routes for a fleet of vehicles in order to satisfy a set of transportation requests. Each request represents a user-specified pickup and delivery location. The PDPTW may be used to model many problems in logistics and public transportation. The location routing problem (LRP) is an extension of the vehicle routing problem where the solution identifies the optimal location of the depots and provides the vehicle schedules and distribution routes. This dissertation seeks to blend the PDPTW and LRP areas of research and formulate a location scheduling pickup and delivery problem with time windows (LPDPTW) in order to model the theater distribution problem and find excellent solutions. This research utilizes advanced tabu search techniques, including reactive tabu search and group theory applications, to develop a heuristic procedure for solving the LPDPTW. Tabu search is a metaheuristic that performs an intelligent search of the solution space. Group theory provides the structural foundation that supports the efficient search of the neighborhoods and movement through the solution space

Modelación En Programación Matemática Y Resolución Del Problema De Localización-Ruteo En Logística Urbana

The implementation of urban distribution centers near to city centers to allow freight consolidation is a widely extended initiative worldwide, seeking to improve traffic congestion and quality of life in downtown, among others. This paper considers the problem of locating urban distribution centers and proposes an exact method, based on integer linear programming for strategic, tactical and operational decision-making. The aim is to solve, in an integer manner, location, sizing and operation (vehicle routing) problems in these logistics platforms. The model is validated using real-data taken from the city of SaintÉtienne, France. Computational experiments are also carried out in order to compare the proposed model with existing procedures from the literature. Results show the efficiency and effectiveness of the proposed model and its applicability in real decision-making for medium sized data sets