A Decision Model for E-commerce-enabled Partial Market Exit

Struggling retail chains often try to recover profitability by closing some of their stores. The challenge in this strategy lies in determining how many stores to close, as store exit has implications for both the customers and the supply chain. After a store closes, its customers are lost forever to the competition, unless there is a surviving open store nearby or an electronic alternative such as an e-store. From the supply chain perspective, after a store closes, its supporting regional distribution center is left with less business, and thus reduced viability. This paper develops a decision support model to study the profitability of alternative retail network structures by varying the proportion of stores that are closed, the average price sensitivity of demand, the price difference between the online store and the traditional retailers, and customer retention rates

Efficient heuristic algorithms for location of charging stations in electric vehicle routing problems

Indexación: Scopus.This work has been partially supported by CONICYT FONDECYT by grant 11150370, FONDEF IT17M10012 and the “Grupo de Logística y Transporte” at the Universidad del Bío-Bío.. This support is gratefully acknowledged.Eco-responsible transportation contributes at making a difference for companies devoted to product delivery operations. Two specific problems related to operations are the location of charging stations and the routing of electric vehicles. The first one involves locating new facilities on potential sites to minimise an objective function related to fixed and operational opening costs. The other one, electric vehicle routing problem, involves the consolidation of an electric-type fleet in order to meet a particular demand and some guidelines to optimise costs. It is determined by the distance travelled, considering the limited autonomy of the fleet, and can be restored by recharging its battery. The literature provides several solutions for locating and routing problems and contemplates restrictions that are closer to reality. However, there is an evident lack of techniques that addresses both issues simultaneously. The present article offers four solution strategies for the location of charging stations and a heuristic solution for fleet routing. The best results were obtained by applying the location strategy at the site of the client (relaxation of the VRP) to address the routing problem, but it must be considered that there are no displacements towards the recharges. Of all the other three proposals, K-means showed the best performance when locating the charging stations at the centroid of the cluster. © 2012-2018. National Institute for R and D in Informatics.https://sic.ici.ro/wp-content/uploads/2018/03/Art.-8-Issue-1-2018-SIC.pd

An MINLP model to support the movement and storage decisions of the Indian food grain supply chain

This paper addresses the novel three stage food grain distribution problem of Public Distribution System (PDS) in India which comprises of farmers, procurement centers, base silos and field silos. The Indian food grain supply chain consists of various activities such as procurement, storage, transportation and distribution of food grain. In order to curb transportation and storage losses of food grain, the Food Corporation of India (FCI) is moving towards the modernized bulk food grain supply chain system. This paper develops a Mixed Integer Non-Linear Programming (MINLP) model for planning the movement and storage of food grain from surplus states to deficit states considering the seasonal procurement, silo capacity, demand satisfaction and vehicle capacity constraints. The objective function of the model seeks to minimize the bulk food grain transportation, inventory holding, and operational cost. Therein, shipment cost contains the fixed and variable cost, inventory holding and operational cost considered at the procurement centers and base silos. The developed mathematical model is computationally complex in nature due to nonlinearity, the presence of numerous binary and integer variables along with a huge number of constraints, thus, it is very difficult to solve it using exact methods. Therefore, recently developed, Hybrid Particle-Chemical Reaction Optimization (HP-CRO) algorithm has been employed to solve the MINLP model. Different problem instances with growing complexities are solved using HP-CRO and the results are compared with basic Chemical Reaction Optimization (CRO) and Particle Swarm Optimization (PSO) algorithms. The results of computational experiments illustrate that the HP-CRO algorithm is competent enough to obtain the better quality solutions within reasonable computational time

Extending the solid step fixed-charge transportation problem to consider two-stage networks and multi-item shipments

This paper develops a new mathematical model for a capacitated solid step fixed-charge transportation problem. The problem is formulated as a two-stage transportation network and considers the option of shipping multiple items from the plants to the distribution centers (DC) and afterwards from DCs to customers. In order to tackle such an NP-hard problem, we propose two meta-heuristic algorithms; namely, Simulated Annealing (SA) and Imperialist Competitive Algorithm (ICA). Contrary to the previous studies, new neighborhood strategies maintaining the feasibility of the problem are developed. Additionally, the Taguchi method is used to tune the parameters of the algorithms. In order to validate and evaluate the performances of the model and algorithms, the results of the proposed SA and ICA are compared. The computational results show that the proposed algorithms provide relatively good solutions in a reasonable amount of time. Furthermore, the related comparison reveals that the ICA generates superior solutions compared to the ones obtained by the SA algorithm

A Two-Echelon Location-inventory Model for a Multi-product Donation-demand Driven Industry

This study involves a joint bi-echelon location inventory model for a donation-demand driven industry in which Distribution Centers (DC) and retailers (R) exist. In this model, we confine the variables of interest to include; coverage radius, service level, and multiple products. Each retailer has two classes of product flowing to and from its assigned DC i.e. surpluses and deliveries. The proposed model determines the number of DCs, DC locations, and assignments of retailers to those DCs so that the total annual cost including: facility location costs, transportation costs, and inventory costs are minimized. Due to the complexity of problem, the proposed model structure allows for the relaxation of complicating terms in the objective function and the use of robust branch-and-bound heuristics to solve the non-linear, integer problem. We solve several numerical example problems and evaluate solution performance

A Survey on the Warehouse Location Problem

The warehouse location problem has assumed numerous formulations, and solutions have been devised using a variety of mathematical techniques. The development of this effort is examined and relevant models presented for evaluation.Supported in part by the Office of Naval Research under contract 67-A-0204-007

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.