A simheuristic for bi-objective stochastic permutation flow shop scheduling problem

This paper addresses the stochastic permutation flow shop problem (SPFSP) in which the stochastic parameters are the processing times. This allows the modeling of setups and machine breakdowns. Likewise, it is proposed a multi-objective greedy randomized adaptive search procedure (GRASP) coupled with Monte-Carlo Simulation to obtain expected makespan and expected tardiness. To manage the bi-objective function, a sequential combined method is considered in the construction phase of the meta-heuristic. Moreover, the local Search combines 2-optimal interchanges with a Pareto Archived Evolution Strategy (PAES) to obtain the Pareto front. Also, some Taillard benchmark instances of deterministic permutation flow shop problem were adapted in order to include the variation in processing times. Accordingly, two coefficients of variation (CVs) were tested: one depending on expected processing times values defined as twice the expected processing time of a job, and a fixed value of 0.25. Thus, the computational results on benchmark instances show that the variable CV provided lower values of the expected makespan and tardiness, while the con-stant CV presented higher expected measures. The computational results present insights for further analysis on the behavior of stochastic scheduling problems for a better approach in real-life scenarios at industrial and service systems

Modelación En Programación Matemática Y Resolución Del Problema De Localización-Ruteo En Logística Urbana

The implementation of urban distribution centers near to city centers to allow freight consolidation is a widely extended initiative worldwide, seeking to improve traffic congestion and quality of life in downtown, among others. This paper considers the problem of locating urban distribution centers and proposes an exact method, based on integer linear programming for strategic, tactical and operational decision-making. The aim is to solve, in an integer manner, location, sizing and operation (vehicle routing) problems in these logistics platforms. The model is validated using real-data taken from the city of SaintÉtienne, France. Computational experiments are also carried out in order to compare the proposed model with existing procedures from the literature. Results show the efficiency and effectiveness of the proposed model and its applicability in real decision-making for medium sized data sets

La utilización de la investigación de operaciones como soporte a la toma de decisiones en el sector salud: Un estado del arte

The contributions of Operations Research (OR) in the healthcare field have been extensively studied in the scientific literature since the 1960s, covering decision support tools with operational, tactical, and strategic approaches. The aim of this article is to analyze the historical development of the application of OR models in healthcare. The application trends for optimization, planning, and decision- making models are studied through a descriptive literature review and a bibliometric analysis of scientific papers published between 1952 and 2016. An upward trend in the usage of operational models is observed with the predominance of resource optimization approaches and strategic decision-making for public health.Los aportes de la Investigación de Operaciones (IO) en el campo de la salud han sido ampliamente estudiados en la literatura científica desde la década de 1960, abarcando herramientas para el soporte a la decisión en enfoques operacionales, tácticos y estratégicos. El objetivo de este artículo es analizar el avance y el desarrollo histórico del uso de modelos operativos en el campo de la salud. A través de una revisión bibliográfica descriptiva y un análisis bibliométrico de artículos científicos publicados durante el periodo 1952-2016, se estudia el comportamiento de las tendencias en la aplicación de modelos operativos para la optimización, la planificación y la toma de decisiones en el sector salud. Se evidencia una tendencia creciente en el uso de modelos de IO durante el periodo estudiado, predominando las aplicaciones orientadas a la optimización de recursos y decisiones estratégicas de salud pública

Simulation-optimization approach for the stochastic location-routing problem

The location routing problem with stochastic transportation cost and vehicle travel speeds is considered in this paper. A hybrid solution procedure based on Ant Colony Optimisation (ACO) and Discrete-Event Simulation (DES) is proposed. After using a sequential heuristic algorithm to solve the location subproblem, the subsequent capacitated vehicle routing problem is solved using ACO. Finally, a DES model evaluates those vehicle routes in terms of their impact on the expected total costs. The approach is tested using well-known randomly generated datasets. Since no previous works in the literature studied exactly the same SLRP, the proposed procedure is compared against its deterministic version. Numerical results show the efficiency and efficacy of the hybrid ACO-DES approach

The storage location assignment problem: A literature review

The storage of goods plays a crucial role in warehouse management systems. Although this operation is often considered simple, it is in fact complex, due to the volume of products, the uncertainty in demands, and the rapid customer service response that the market requires. Moreover, the optimization of logistical resources to maintain an efficient operational flow, such as the allocation of storage spaces, often requires complex decisions. In this paper, we analyze academic contributions on the storage location assignment problem published between 2005 and 2017. The literature is classified according to the solution methods, objectives, and related considerations. Suggestions are also provided for future research

Un procedimiento de búsqueda voraz adaptativo probabilista para un problema monoproducto de localización de instalaciones no capacitado

AbstractThis paper considers the three-echelon uncapacitated facility location problem (TUFLP), which consists on both defining the flow of products from manufacturing plants to clients via a set of warehouses and the location of such warehouses. The objective function is to minimize the total cost of warehouse location and production and distribution. Since the problem is NP-hard, this paper proposes a Greedy Randomized Search Procedure (GRASP) to solve the single-item case. Computational experiments are conducted using known instances from the literature. Results show that the proposed algorithm performs well obtaining very good solutions (and even optimal values) in less computational time than an exact method based on mixed-integer linear programming.ResumenEste artículo considera el problema de localización de instalaciones no capacitado en una cadena logística de tres eslabones (Three-echelon Uncapacitated Facility Location Problem, TUFLP). El problema de optimización consiste en definir los flujos de productos desde las plantas de manufactura hacia los clientes a través de centros de distribución (CD), cuya ubicación debe determinarse adicionalmente. La función objetivo es la minimización del costo total conformado por el costo fijo de localización de los centros de distribución y los costos variables de producción y distribución de productos. Puesto que este es un problema NP-completo, se propone la utilización de un procedimiento voraz adaptativo probabilista (GRASP) para resolver el caso particular monoproducto. Se desarrollan experimentos computacionales con instancias conocidas en la literatura.Los resultados muestran que el algoritmo propuesto permite obtener buenas soluciones (e incluso valores óptimos) en menor tiempo de cálculo que un procedimiento exacto basado en programación lineal entera mixta

A Methodology to Anticipate the Activity Level of Collaborative Networks: The Case of Urban Consolidation Centers

This article presents a methodology relative to the assessment of a particular measure in city logistics: Urban Consolidation Centers (UCCs). We identify that this kind of collaborative network is, often, poorly evaluated and thus operates in a way that is neither sustainable nor efficient. By mobilizing several fields of knowledge, such as operational research, game theory, and transportation studies on real cases, we propose a solution to anticipate the activity level of a UCC and determine the condition under which it generates benefits for carriers. The aim is to provide a suitable aid to public decision makers in territorial management. The study concludes by an application of the method on the test case of the city of Saint-Etienne, France

The location routing problem with facility sizing decisions

The location routing problem (LRP) integrates operational decisions on vehicle routing operations with strategic decisions on the location of the facilities or depots from which the distribution will take place. In other words, it combines the well-known vehicle routing problem (VRP) with the facility location problem (FLP). Hence, the LRP is an NP-hard combinatorial optimization problem, which justifies the use of metaheuristic approaches whenever large-scale instances need to be solved. In this paper, we explore a realistic version of the LRP in which facilities of different capacities are considered, i.e., the manager has to consider not only the location but also the size of the facilities to open. In order to tackle this optimization problem, three mixed-integer linear formulations are proposed and compared. As expected, they have been proved to be cost- and time- inefficient. Hence, a biased-randomized iterated local search algorithm is proposed. Classical instances for the LRP with homogeneous facilities are naturally extended to test the performance of our approach.Peer ReviewedPostprint (published version