Combining heuristics with simulation and fuzzy logic to solve a flexible-size location routing problem under uncertainty

The location routing problem integrates both a facility location and a vehicle routing problem. Each of these problems are NP-hard in nature, which justifies the use of heuristic-based algorithms when dealing with large-scale instances that need to be solved in reasonable computing times. This paper discusses a realistic variant of the problem that considers facilities of different sizes and two types of uncertainty conditions. In particular, we assume that some customers’ demands are stochastic, while others follow a fuzzy pattern. An iterated local search metaheuristic is integrated with simulation and fuzzy logic to solve the aforementioned problem, and a series of computational experiments are run to illustrate the potential of the proposed algorithm.This work has been partially supported by the Spanish Ministry of Science (PID2019-111100RB-C21/AEI/10.13039/501100011033). In addition, it has received the support of the Doctoral School at the Universitat Oberta de Catalunya (Spain) and the Universidad de La Sabana (INGPhD-12-2020).Peer ReviewedPostprint (published version

A multi-objective possibilistic programming approach for locating distribution centers and allocating customers demands in supply chains

In this paper, we present a multi-objective possibilistic programming model to locate distribution centers (DCs) and allocate customers' demands in a supply chain network design (SCND) problem. The SCND problem deals with determining locations of facilities (DCs and/or plants), and also shipment quantities between each two consecutive tier of the supply chain. The primary objective of this study is to consider different risk factors which are involved in both locating DCs and shipping products as an objective function. The risk consists of various components: the risks related to each potential DC location, the risk associated with each arc connecting a plant to a DC and the risk of shipment from a DC to a customer. The proposed method of this paper considers the risk phenomenon in fuzzy forms to handle the uncertainties inherent in these factors. A possibilistic programming approach is proposed to solve the resulted multi-objective problem and a numerical example for three levels of possibility is conducted to analyze the model

A taxonomy for emergency service station location problem

The emergency service station (ESS) location problem has been widely studied in the literature since 1970s. There has been a growing interest in the subject especially after 1990s. Various models with different objective functions and constraints have been proposed in the academic literature and efficient solution techniques have been developed to provide good solutions in reasonable times. However, there is not any study that systematically classifies different problem types and methodologies to address them. This paper presents a taxonomic framework for the ESS location problem using an operations research perspective. In this framework, we basically consider the type of the emergency, the objective function, constraints, model assumptions, modeling, and solution techniques. We also analyze a variety of papers related to the literature in order to demonstrate the effectiveness of the taxonomy and to get insights for possible research directions

A queuing location-allocation model for a capacitated health care system

International audienceThe aim of the present paper is to propose a location-allocation model for a capacitated health care system. This paper develops a discrete modeling framework to determine the optimal number of facilities among candidates and optimal allocations of the existing customers to operating health centers in a coverage distance. In doing so, the total sum of customer and operating facility costs is minimized. Our goal is to create a model that is more practical in the real world. Therefore, setup costs of hospitals are based on the costs of customers, xed costs of establishing health centers, and costs based on the available resources in each level of hospitals. In this paper, the idea of hierarchical structure has been used. There are two levels of service in hospitals, including low and high levels, and sections at diierent levels that provide diierent types of services. The patients refer to diierent sections of the hospital according to their requirements. To solve the model, two meta-heuristic algorithms, including genetic and simulated annealing algorithms and their combination, are proposed. To evaluate the performance of the three algorithms, some numerical examples are produced and analyzed using the statistical test in order to determine which algorithm works better

A new bi-objective model of the urban public transportation hub network design under uncertainty

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Fleet dimensioning and scheduling in the Brazilian ethanol industry: a fuzzy logic approach

This work solves a real-world multi-depot vehicle routing problem (MDVRP) with a homogeneous fleet and capacitated depots. A pipeline company wants to establish a vehicle policy in order to own part of its fleet and serve its customers for a period of one year. The company also wants to know the schedule of the visits for collecting ethanol from 261 producers and taking it to their three terminals located in Brazil. This problem presents uncertain demand, since weather conditions impact the final crop and uncertain depot capacity. Due to the vagueness of managers’ speech, this problem also presents uncertain travel time. In this paper, fuzzy logic is used to model uncertainty and vagueness and to split the initial instance into smaller ones. Besides solving a real-world problem with fuzzy demand, fuzzy depot capacity and fuzzy travel time, this paper contributes with a decision making tool that reports different solutions for different uncertainty levels.Este trabalho resolve um problema de roteamento de veículos multi-depósito do mundo real (MDVRP) com frota homogênea e depósitos capacitados. Uma empresa de pipeline deseja estabelecer uma política de veículos para possuir parte de sua frota e atender seus clientes por um período de um ano. A empresa também quer saber o agendamento das visitas para coleta de etanol de 261 produtores e retirada para seus três terminais localizados no Brasil. Este problema apresenta incertezas de demanda, já que as condições climáticas impactam a safra final e depósito de capacidade incerta. Devido à imprecisão do discurso dos gerentes, este problema também apresenta tempo de viagem incerto. Neste artigo, a lógica fuzzy é usada para modelar a incerteza e vagueza e dividir a instância inicial em outras menores. Além de resolver um problema do mundo real com demanda difusa, capacidade de depósito difusa e tempo de viagens difusas, este artigo contribui com uma ferramenta de tomada de decisão que relata diferentes soluções para diferentes níveis de incerteza

A HYBRID ALGORITHM FOR THE UNCERTAIN INVERSE p-MEDIAN LOCATION PROBLEM

In this paper, we investigate the inverse p-median location  problem with variable edge lengths and variable vertex weights on networks in which the vertex weights and modification costs are the independent uncertain variables. We propose a  model for the uncertain inverse p-median location problem  with tail value at risk objective. Then, we show that  it  is NP-hard. Therefore,  a hybrid particle swarm optimization  algorithm is presented  to obtain   the approximate optimal solution of the proposed model. The algorithm contains expected value simulation and tail value at risk simulation

The design of cement distribution network in Myanmar : a case study of "X" cement industry

The network design problem is one of the most comprehensive strategic decision issues that need to be optimized for the long-term efficient operation of whole supply chain. The problem treated in this thesis is a capacitated location allocation planning of distribution centers for the distribution network design. The distribution network in this research is considered from plants to distribution centers and distribution centers to demand points. The research will explore the optimal number and locations of cement distribution center of “X” cement industry in Myanmar. The Mixed Integer Linear Programming (MILP) was developed as a tool to solve optimization problem which involves 3 manufacturing plants, 6 distribution centers and 6 market regions. The data collection was done by the company. The (MILP) model provides useful information for the Company about which distribution centers should be opened and what would be the best distribution network in order to maximize profit while still satisfies the customers’ demand. In this study, we proposed three scenarios which are scenario two, six and eight. In all scenarios, the solution was to have only two distribution centers from Mandalay and Meikhtila markets are recommended to open in the distribution network

The Incremental Cooperative Design of Preventive Healthcare Networks

This document is the Accepted Manuscript version of the following article: Soheil Davari, 'The incremental cooperative design of preventive healthcare networks', Annals of Operations Research, first published online 27 June 2017. Under embargo. Embargo end date: 27 June 2018. The final publication is available at Springer via http://dx.doi.org/10.1007/s10479-017-2569-1.In the Preventive Healthcare Network Design Problem (PHNDP), one seeks to locate facilities in a way that the uptake of services is maximised given certain constraints such as congestion considerations. We introduce the incremental and cooperative version of the problem, IC-PHNDP for short, in which facilities are added incrementally to the network (one at a time), contributing to the service levels. We first develop a general non-linear model of this problem and then present a method to make it linear. As the problem is of a combinatorial nature, an efficient Variable Neighbourhood Search (VNS) algorithm is proposed to solve it. In order to gain insight into the problem, the computational studies were performed with randomly generated instances of different settings. Results clearly show that VNS performs well in solving IC-PHNDP with errors not more than 1.54%.Peer reviewe