Optimal Dislocation of Branch Offices From View of Transport Availability

The district authorities were canceled and substituted by self-governments branch offices after the public administration reform in the Czech Republic. So-called municipalities with extended sphere of authority were proposed for placing of branch offices. These branch offices were chosen regardless of their transport availability. The article deals with the problem of determination of optimal number of branch offices and of their attract areas, from view of their transport availability. The problem is solved with the methods of mathematical programming. The problem was by the help of Lagrange multiplicator converted to incapacitated location problem with criterion function sum(fyi)+sum sum (cij xij) where xij is arbitrary variable expressing whether the municipality j is allocated to the branch office i, cij is a coefficient representing distance from branch office i, weighted with population of the municipality j, yi is bivalent variable expressing whether in the municipality will be established the branch office and f is constant presenting branch office establishment costs. Model is solved with Erlenkotter method realized by the help of BB dual algorithm.

A computational comparison of several formulations for the multi-period incremental service facility location problem

The Multi-period Incremental Service Facility Location Problem, which was recently introduced, is a strategic problem for timing the location of facilities and the assignment of customers to facilities in a multi-period environment. Aiming at finding the strongest formulation for this problem, in this work we study three alternative formulations based on the so-called impulse variables and step variables. To this end, an extensive computational comparison is performed. As a conclusion, the hybrid impulse–step formulation provides better computational results than any of the other two formulations

Distribution Network Configuration Considering Inventory Cost

Inter-city distribution network structure is considered as one of which determine the quantity of economic activities in each city. In the field of operations research, several types of optimal facility location problem and algorithms for them have been proposed. Such problems typically minimize the logistic cost with given inter-city transportation cost and facility location cost. But, when we take inventory to coop with fluctuating demands into account, facility size becomes different for each location reflecting the level of uncertainty of demand there. As observed in many developed countries, customers require more variety of commercial goods, and we must prepare more number of commercial goods. Moreover, life length of each product becomes shorter. Without highly organized management, large inventory for many products yield large risk of depreciation of commercial value as well as large cost for floor space for stocking. Considering those, inventory cost should be explicitly considered in distribution network configuration problem. There is an essential trade off between inventory cost and transportation cost: when you set smaller number of distribution center having thicker demands there, relative stock size to coop with fluctuations become small and then, we need less inventory cost. But such concentrated location pattern results longer transportation to the customers and larger transportation cost. Nozick and Turnquist(2001) formulated a two-echelon distribution network formation problem considering inventory cost at plant and distribution centers. They used optimal inventory assignment considering the expected penalty of distribution center stock-out and plant stock-out. Stock-out was considered as the situation when Poisson distributed demand exceeded stock size, and the mean demand there was given by optimal facility location model. Inventory size of distribution center alters the location cost of distribution center, therefore optimal facility location problem was refreshed and solved again. The paper proposed iterative algorithm to get optimal inventory locations. Our paper expands their model in two ways; first we admit the difference of unit location cost for distribution centers by geographical locations, and secondly, we consider different uncertainties for customer orders by departing from simple Poisson distribution. The first alternation gives new explanation for the following situations: highly dense metropolitan regions have relatively larger number of centers and smaller coverage of each center. But such propensity usually contradicts with the land price; then center location should be limited considering higher land price in metropolitan areas. Then the optimal locations cannot be prospected in straight forwardly. The second model expansion allows our model to analyze how regularity of demands affects on the network structure. Our paper applies the model to the realistic Japanese transportation network, and show which cities may possess distribution center function in the nationwide distribution network. Without the back-stock in plant level, each distribution center must prepare inventory for their demand, but such inventory sometime requires unrealistic large location cost in metropolitan area such as Tokyo. On the other hand, if distribution center can rely on the back stock in plant, the centers in metropolitan regions stand without their own inventory.

Solving the p-median location problem with the Erlenkotter approach in public service system design

The problem can be often formulated as a weighted p-median problem. Real instances of the problem are characterized by big numbers of possible service center locations, which can take the value of several hundreds or thousands. The optimal solution can be obtained by the universal IP solvers only for smaller instances of the problem. The universal IP solvers are very time-consuming and often fail when solving a large instance. Our approach to the problem is based on the Erlenkotter procedure for solving of the uncapacitated facility location problem and on the Lagrangean relaxation of the constraint which limits number of the located center. The suggested approach finds the optimal solution in most of the studied instances. The quality and the feasibility of the resulting solutions of the suggested approach depend on the setting of the Lagrangean multiplier. A suitable value of the multiplier can be obtained by a bisection algorithm. The resulting multiplier cannot guarantee an optimal solution, but provides a near-to-optimal solution and a lower bound. If our approach does not obtain the optimal solution, then a heuristic improves the near-to-optimal solution. The resulting solution of our approach and the optimal solution obtained by the universal IP solver XPRESS-IVE are compared in the computational time and the quality of solutions

Branch and peg algorithms for the simple plant location problem

The simple plant location problem is a well-studied problem in combinatorial optimization. It is one of deciding where to locate a set of plants so that a set of clients can be supplied by them at the minimum cost. This problem of ten appears as a subproblem in other combinatorial problems. Several branch and bound techniques have been developed to solve these problems. In this paper we present a few techniques that enhance the performance of branch and bound algorithms. The new algorithms thus obtained are called branch and peg algorithms, where pegging refers to assigning values to variables outside the branching process. We present exhaustive computational experiments which show that the new algorithms generate less than 60% of the number of subproblems generated by branch and bound algorithms, and in certain cases require less than 10% of the execution times required by branch and bound algorithms.

A Parallelizable Acceleration Framework for Packing Linear Programs

This paper presents an acceleration framework for packing linear programming problems where the amount of data available is limited, i.e., where the number of constraints m is small compared to the variable dimension n. The framework can be used as a black box to speed up linear programming solvers dramatically, by two orders of magnitude in our experiments. We present worst-case guarantees on the quality of the solution and the speedup provided by the algorithm, showing that the framework provides an approximately optimal solution while running the original solver on a much smaller problem. The framework can be used to accelerate exact solvers, approximate solvers, and parallel/distributed solvers. Further, it can be used for both linear programs and integer linear programs

Returnable containers: an example of reverse logistics

Considers the application of returnable containers as an example of reverse logistics. A returnable container is a type of secondary packaging that can be used several times in the same form, in contrast with traditional cardboard boxes. For this equipment to be used, a system for the return logistics of the containers should be available: this system should guarantee that the containers are transported from the recipients to the next senders, and that they are cleaned and maintained, if necessary. Outlines several ways in which the return of these containers can be organized. Also includes a case study involving the design of such a return logistic system in The Netherlands. Also describes a quantitative model that can be used to support the related planning process

Warehouse Location Decision in Pakistan:A Real Case Study

The manufacturing industry in Pakistan ispassing through a critical phase of its history. In the changing market placeconsumer are increasingly vigilant and demanding better quality, morecompetitive prices and shorter lead times. Maintaining cost effectivemanufacturing along with it distribution to the different customers across thecountry is becomes challenging day by day. In this paper, we propose anadditional new warehouse location in Pakistan using transportation cost as adecision factor. Initially the proposed warehouse will be run by the third partywarehouse service provider on temporary basis, so that it lower down theinventory level of Lahore warehouse from 0.4 million liters to 0.2 millionliters, saves approximately 1.5 Million Rs. / year with improved customerservice