Location Planning of Field Ammunition Depot for Multi-stage Supply Based on Dijstra Algorithm

The location of field ammunition depots is related to the efficiency and effectiveness of ammunition supply and support, and is affected by the changing needs of different stages of operations. In response to complex situations such as damage to transportation roads, repairs, and dynamic changes in demand in the course of combat, the fastest supply speed is the primary goal, while the satisfaction rate, balance, and cost factors of the ammunition supply at each demand point are taken into account to build a multi-stage supply Site selection planning model for field ammunition depot. Use Dijstra algorithm’s hierarchical sequence method to determine the shortest supply time, gradually increase the supply time, find the relationship between supply time, satisfaction rate, balance and cost, and find a satisfactory location plan. Finally, the simulation case calculations show that the model can cover some key dynamic changes during wartime, with strong adaptability and more scientific site selection.

A Hybrid Strategic Oscillation with Path Relinking Algorithm for the Multiobjective k-Balanced Center Location Problem

This paper presents a hybridization of Strategic Oscillation with Path Relinking to provide a set of high-quality nondominated solutions for the Multiobjective k-Balanced Center Location problem. The considered location problem seeks to locate k out of m facilities in order to serve n demand points, minimizing the maximum distance between any demand point and its closest facility while balancing the workload among the facilities. An extensive computational experimentation is carried out to compare the performance of our proposal, including the best method found in the state-of-the-art as well as traditional multiobjective evolutionary algorithms.

Using NSGA-II to solve multi-objective competitive location problem with cooperative coverage for distance-based attractiveness

Multi-objective competitive location problem with cooperative coverage for distance-based attractiveness is introduced in this paper. The potential facilities compete to be selected to serve all demand points which are determined by maximizing total collective attractiveness of all demand points from assigned facilities and minimizing the fixed and distance costs between all demand points and selected facilities. Facility attractiveness is represented as a coverage of the facility with full, partial and none coverage corresponding to maximum full and partial coverage radii. Cooperative coverage, which the demand point is covered by at least one facility, is also considered. The problem is formulated as a multi-objective optimization model and solution procedure based on elitist non-dominated sorting genetic algorithms (NSGA-II) is developed. Experimental example demonstrates the best non-dominated solution sets obtained by developed solution procedure. Contributions of this paper include introducing competitive location problem with facility attractiveness as a distance-based coverage of the facility, re-categorizing facility coverage classification and developing solution procedure base upon NSGA-II.

Factors Influencing the Unemployment Rate in Romania During 1997-2019

"Current macroeconomic theories examine the problem of unemploy-ment rate from the aggregate demand point of view. Rising unem-ployment is always seen as a sign of the weak economy, where is a slow growth and also little spending. These might trigger actions by au-thorities to help reduce unemployment, by increasing the nation's money supply, so it can boost the economy. Among the factors that in-fluence (un-)employment, at least two very important should be taken in consideration: exchange rate and inflation. The research aims to ana-lyse the impact of inflation, the RON / EURO exchange rate and the fi-nancial crisis on unemployment rate in Romania during January 1997- March 2019. Keywords: unemployment rate, exchange rate, inflation rate JEL Codes: E24, F31, E31"

Optimization Model Based on Reachability Guarantee for Emergency Facility Location and Link Reinforcement

The reasonable location of emergency facilities plays an important role in both predisaster service and postdisaster relief. Moreover, damage to the transportation network often affects the accessibility of demand points, which can seriously hamper timely rescue operations. Reasonable location of emergency facilities and reinforcement of fragile roads are two important strategies to improve the reachability of demand points. In this paper, we proposed a biobjective optimization model to determine locations of emergency facilities and links to be reinforced given a limited budget. Each demand point is allocated a primary facility and a backup facility, the former can provides normal service, and the latter is prepared for postdisaster relief. One goal of the model is to minimize the operating cost of normal services, and another goal is to maximize the reachability guarantee of demand points. The novelty and contribution of this paper are that we defined the reachability by introducing damage tolerance instead of link failure probability. Based on this, we defined the reachability guarantee to deal with the worst scenario of disasters. By embedding the max-flow problem of the reachability guarantee into the emergency facility location problem, the locations of emergency facilities and links to be reinforced can be determined simultaneously. The methodology is applied to a simplified Sioux Falls transportation network. Results such as the trade-off curve of two goals, budget efficiency, and the effect of reinforcement demonstrated the effectiveness of the model.

Solving Capacitated Facility Location Problem Using Lagrangian Decomposition and Volume Algorithm

In this research, we will focus on one variant of the problem: the capacitated facility location problem (CFLP). In many formulations of the CFLP, it is assumed that each demand point can be supplied by only one open facility, which is the simplest case of the problem. We consider the case where each demand point can be supplied by more than one open facility. We first investigate a Lagrangian relaxation approach. Then, we illustrate in the problem decomposition how to introduce tighter constraints, which solve the CFLP faster while achieving a better quality solution as well. At the same time, we apply the volume algorithm to improve both the lower and the upper bound on the optimum solution of the original problem for the large problem size.

An exact approach for the r-interdiction median problem with fortification

We study the r-interdiction median problem with fortification (RIMF), which considers demand points that are served by facilities. If a facility is interdicted, it can not serve any demand point, increasing the total system cost. To avoid an interdiction, a facility can be fortified. The problem consists of fortifying facilities knowing that some facilities will be interdicted. We propose a branch-and-cut algorithm for the RIMF and several experiments attest that our method outperforms the best exact algorithm found.

Pengembangan Model Capacitated Maximal Covering Location Problem (CMCLP) Dalam Penentuan Lokasi Pendirian Gudang

A strategic location is a place for facility location that built and is able to give maximum advantages for the company. The problem of deciding location is important in optimization area. In general, the solution of that problem focuses on facility placement that is able to minimize or maximizing distribution time, distance, transportation cost or another parameter. Therefore, an appropriate model is needed to determine the strategic location of warehouse establishment. The purpose of this research is to develop a Capacitated Maximal Covering Location Problem (MCLP) model that can be used in determining the location of warehouse establishment that can maximize the number of demands that can be served. From the model, the company not only finds the optimum location to establish the facility but also they can know the number of goods allocated from the distribution center to each demand point as well as the maximum number of demand that can be served.