Supply facility and input/output point locations in the presence of barriers

This paper studies a facility location model in which two-dimensional Euclidean space represents the layout of a shop floor. The demand is generated by fixed rectangular-shaped user sites and served by a single supply facility. It is assumed that (i) communication between the supply point and a demand facility occurs at an input/output (I/O) point on the demand facility itself, (ii) the facilities themselves pose barriers to travel and (iii) distance measurement is as per the L1-metric. The objective is to determine optimal locations of the supply facility as well as I/O points on the demand facilities, in order to minimize total transportation costs. Several, increasingly more complex, versions of the model are formulated and polynomial time algorithms are developed to find the optimal locations in each case. Scope and purpose In a facility layout setting, often a new central supply facility such as a parts supply center or tool crib needs to be located to serve the existing demand facilities (e.g., workstations or maintenance areas). The demand facilities are physical entities that occupy space, that cannot be traveled through, and that receive material from the central facility, through a perimeter I/O (input/output or drop-off/pick-up) point. This paper addresses the joint problem of locating the central facility and determining the I/O point on each demand facility to minimize the total material transportation cost. Different versions of this problem are considered. The solution methods draw from and extend results of location theory for a class of restricted location problems. For practitioners, simple results and polynomial time algorithms are developed for solving these facility (re) design problems

Polynomially solvable cases of multifacility distance constraints on cyclic networks

Ankara : The Department of Industrial Engineering and the Institute of Engineering and Sciences of Bilkent Univ., 1993.Thesis (Master's) -- Bilkent University, 1993.Includes bibliographical references leaves 79-81Distance Constraints Problem is to locate one or more new facilities on a network so that the distances between new and existing facilities as well as between pairs of new facilities do not exceed given upper bounds. The problem is AfV-Complete on cyclic networks and polynomially solvable on trees. Although theory for tree networks is well-developed, there is virtually no theory for cyclic networks. In this thesis, we identify a special class of instances for which we develop theory and algorithms that are applicable to any metric space defining the location space. We require that the interaction between new facilities has a tree structure. The method is based on successive applications of EXPANSION and INTERSECTION operations defined on subsets of the location space. Application of this method to general networks yields strongly polynomial algorithms. Finally, we give an algorithm that constructs an e-optimal solution to a related minimax problem.Yeşilkökçen, Naile GülcanM.S

Optimal location of single and multiple obnoxious facilities: Algorithms for the maximin criterion under different norms.

This thesis investigates the computational problem of locating obnoxious (undesirable) facilities in a way that minimizes their effect on a given set of clients (e.g. population centres). Supposing that the undesirable effects of such a facility on a given client are a decreasing function of the distance between them the objective is to locate these facilities as far away as possible from the given set of clients, subject to constraints that prevent location at infinity. Emphasis is given to the MAXIMIN criterion which is to maximize the minimum client-to-facility distance. Distances are measured either in the Euclidean or the rectilinear metric. The properties of the optimal solution to the single facility problem are viewed from different, seemingly unrelated, perspectives ranging from plane geometry to duality theory. In particular, duality results from a mixed integer programming model are used to derive new properties of the optimal solution to the rectilinear problem. A new algorithm is developed for the rectilinear problem where the feasible region is a convex polygon. Unlike previous approaches, this method does not require linear programming at all. In addition to this, an interactive graphical approach is proposed as a site-generation tool used to identify potential locations in realistic problems. Its main advantages are that it requires minimal user intervention and makes no assumptions regarding the feasible region. It has been applied in large scale problems with up to 1000 clients, whereas the largest reported application so far involved 10 clients. Alternative models are presented for the multi-facility problem as well. Each of them is based on different assumptions and is applicable to specific situations. Moreover, an algorithm is established for the two-facility problem based on the properties of the optimal solution. To the best of our knowledge this is the first attempt to address this problem in the plane. Finally, a number of unresolved issues, especially in the multi-facility problem, are outlined and suggested as further research topics

An allocation based modeling and solution framework for location problems with dense demand /

In this thesis we present a unified framework for planar location-allocation problems with dense demand. Emergence of such information technologies as Geographical Information Systems (GIS) has enabled access to detailed demand information. This proliferation of demand data brings about serious computational challenges for traditional approaches which are based on discrete demand representation. Furthermore, traditional approaches model the problem in location variable space and decide on the allocation decisions optimally given the locations. This is equivalent to prioritizing location decisions. However, when allocation decisions are more decisive or choice of exact locations is a later stage decision, then we need to prioritize allocation decisions. Motivated by these trends and challenges, we herein adopt a modeling and solution approach in the allocation variable space.Our approach has two fundamental characteristics: Demand representation in the form of continuous density functions and allocation decisions in the form of service regions. Accordingly, our framework is based on continuous optimization models and solution methods. On a plane, service regions (allocation decisions) assume different shapes depending on the metric chosen. Hence, this thesis presents separate approaches for two-dimensional Euclidean-metric and Manhattan-metric based distance measures. Further, we can classify the solution approaches of this thesis as constructive and improvement-based procedures. We show that constructive solution approach, namely the shooting algorithm, is an efficient procedure for solving both the single dimensional n-facility and planar 2-facility problems. While constructive solution approach is analogous for both metric cases, improvement approach differs due to the shapes of the service regions. In the Euclidean-metric case, a pair of service regions is separated by a straight line, however, in the Manhattan metric, separation takes place in the shape of three (at most) line segments. For planar 2-facility Euclidean-metric problems, we show that shape preserving transformations (rotation and translation) of a line allows us to design improvement-based solution approaches. Furthermore, we extend this shape preserving transformation concept to n-facility case via vertex-iteration based improvement approach and design first-order and second-order solution methods. In the case of planar 2-facility Manhattan-metric problems, we adopt translation as the shape-preserving transformation for each line segment and develop an improvement-based solution approach. For n-facility case, we provide a hybrid algorithm. Lastly, we provide results of a computational study and complexity results of our vertex-based algorithm

An elliptical cover problem in drone delivery network design and its solution algorithms

Given n demand points in a geographic area, the elliptical cover problem is to determine the location of p depots (anywhere in the area) so as to minimize the maximum distance of an economical delivery trip in which a delivery vehicle starts from the nearest depot to a demand point, visits the demand point and then returns to the second nearest depot to that demand point. We show that this problem is NP-hard, and adapt Cooper’s alternating locate-allocate heuristic to find locally optimal solutions for both the point-coverage and area-coverage scenarios. Experiments show that most locally optimal solutions perform similarly well, suggesting their sufficiency for practical use. The one-dimensional variant of the problem, in which the service area is reduced to a line segment, permits recursive algorithms that are more efficient than mathematical optimization approaches in practical cases. The solution also provides the best-known lower bound for the original problem at a negligible computational cost

The continuous single source location problem with capacity and zone-dependent fixed cost: Models and solution approaches

The continuous capacitated single-source multi-facility Weber problem with the presence of facility fixed cost is investigated. A new mathematical model which incorporates multi-level type capacity (or design) and facility fixed cost that is capacity-based and zone-dependent is introduced. As no data set exists for this new location problem, a new data set based on convex polygons using triangular shape is constructed. A generalised two stage heuristic scheme that combines the concept of aggregation, an exact method, and an enhanced Cooper’s alternate location-allocation method is put forward. A framework that embeds Variable Neighbourhood Search is also proposed. Computational experiments show that these matheuristics produce encouraging results for this class of location problems. The proposed approaches are also easily adapted to cater for a recently studied variant namely the single-source capacitated multi-facility Weber problem where they outperform those recently published solution method

Localización simple de servicios deseados y no deseados en redes con múltiples criterios

Análisis y desarrollo de varios modelos de localización de servicios deseados y no deseados en redes con múltiples criterios. Asimismo, se han propuesto algunas mejoras en modelos de localización de servicios no deseados en redes con un solo criterio. Por consiguiente, con respecto a la localización de servicios deseados sobre redes, se propone un algoritmo polinomial para solucionar el problema del cent-dian biobjetivo. También se ha estudiado la localización de un servicio en una red con múltiples objetivos tipo mediana. Asimismo, se ha desarrollado un algoritmo polinomial para solucionar el problema cent-dian multicriterio en redes con múltiples pesos por nodo y múltiples longitudes por arista. Con respecto a los problemas de localización de servicios no deseados, primero tratamos el problema de localización del 1-centro no deseado en redes. Demostramos que las cotas superiores ya propuestas en trabajos anteriores pueden ser ajustadas. Por medio de una formulación más adecuada del problema, se ha desarrollado un nuevo algoritmo polinomial el cual es más sencillo y computacionalmente más rápido que los ya divulgados en la literatura. También se ha analizado el problema de localizar una mediana no deseada en una red, obteniendo una nueva y mejor cota superior. Se presenta un nuevo algoritmo para solucionar este problema. Por otra parte, siguiendo la resolución del problema maxian, también se ha propuesto un nuevo algoritmo para solucionar el problema del anti-cent-dian en redes. Finalmente, se han estudiado los problemas del centro no deseado y de la mediana no deseada en redes multicriterio, estableciendo nuevas propiedades y reglas para eliminar aristas ineficientes. También se presenta el modelo anti-cent-dian como combinación convexa de los dos últimos problemas. Se propone una regla eficaz para quitar aristas que contienen puntos ineficientes, así como un algoritmo polinomial. Además, este modelo se puede modificar ligeramente para generalizar otros modelos presentados en la literatura