Exploration & Exploitation: Reconciling Product Innovation and Supply Chain Performance in Consumer Packaged Goods Manufacturing

Product innovation often introduces complexity within supply chains, hurting operational efficiency –yet companies must be innovative to survive. That is the central issue of this thesis. We analyze the innovation vs. efficiency trade-off from the supply chain perspective using multiple research methods and the lenses of the exploration & exploitation literature, aiming at developing a framework for dealing with product portfolio exploration & exploitation issues in consumer packaged goods (CPG) manufacturing operations.We conducted a thorough, systematic review of the relevant literature related exploration & exploitation and identified that operations management, being the discipline that deals with getting things done, may be the next frontier of this multidisciplinary research stream. We then empirically analyzed the impact of new product introductions on supply chain performance, using qualitative and quantitative methods: we identified the nuances of how this impact flows and also tested and measured the impact using cross-sectional-longitudinal operational data. We finally conducted an action research project in order to analyze how to build exploration-and-exploitation-enabling supply chain strategies.We found evidence that new product introductions imply an impact on supply chain performance; yet it mostly goes through the increased variability of production assortment and is associated with category-based long-term impacts. We claim that, for small businesses and single business units aiming to be both innovative and efficient, supply chain strategies should incorporate certain conflicting goals; however, certain actions can be taken to mitigate the negative impact of concurrent goals interfering into one another.This study contributes to the exploration & exploitation literature by: (1) analyzing and summarizing the evolution of the literature stream, being among the first to do it from the operations management perspective; (2) evaluating how new product introductions impact supply chain performance in a CPG manufacturing firm, providing a set of testable hypotheses; (3) testing and measuring the short-term and long-term impact of new product introductions on the supply chain performance in CPG manufacturing operations using robust panel data econometrics; (4) testing the moderation effects of product-level degree of innovativeness on the relationship between new product introductions and supply chain performance; (5) adding a different level of analysis –i.e. product category– to dealing with new product introductions; (6) employing the Conceptual System Assessment and Reformulation (CSAR) as a research method for the first time; and (7) unveiling a set of supply chain trade-offs that can be faced by CPG manufacturing companies willing to be both innovative and efficient, also challengingthe notion that a good supply chain strategy must be free of conflicting goals.This research is also carries managerial implications, as it: (1) provides a summary of the relevant literature on exploration & exploitation, which can be a helpful source for practitioners willing to overcome this dilemma; (2) improves the understanding about the how new product introductions impact supply chain performance; (3) quantifies the impact of new product introductions on supply chain performance, which can be a helpful decision-making tool when balancing exploration & exploitation; (4) improves managerial intuition for the conditional supply chain implications of product-level degree of innovativeness when introducing new products; and (5) provides guidance for building supply chain strategies to balance exploration & exploitation in CPG manufacturing firms.<br /

An alternative solution for the repair of electrical breakdowns after natural disasters based on ant colony optimization

Abundant literature is available for the route planning based on meta-heuristic algorithms. However, most researches in this field are developed under normal scenarios (e.g. normal weather conditions). The natural disasters, such as hurricanes, on the contrary, impose hard constraints to these combinatorial problems. In this paper, a route-planning problem is solved, specifically, for the repair of electrical breakdowns that occur after natural disasters. The problem is modeled using an assignment-based integer programming formulation proposed for the Multiple Traveling Salesman Problem (mTSP). Moreover, this paper proposes the creative application of an algorithm based on Ant Colony Optimization (ACO), specifically Multi-type Ant Colony System (M-ACS), where each colony represents a set of possible global solutions. Ants cooperate and compete by means of “frequent” pheromone exchanges aimed to find a solution. The algorithm performance has been compared against other ACO variant, showing the efficacy of the proposed algorithm on realistic decision-making

Environmental performance evaluation under a green supply chain approach

Among the environmental management approaches, the concept of Green Supply Chain Management (GSCM) has become one of the most important in recent years. The GSCM approach addresses all processes and activities that make up the supply chain echelons (procurement, manufacturing and delivery), also including design, purchasing, marketing and reverse logistics. Although the literature review identified the existence of a variety of environmental performance indicators framed the Pressure-State-Response approach, indicators applied under the GSCM approach were not found. Therefore, this paper presents a methodology for the construction of a multicriteria indicator to measure the environmental performance under the GSCM approach, based on 8 processes and 32 activities identified from the literature review. The indicator was applied in a group of 14 companies in the coffee region of Colombia. The results indicate a heterogeneous performance among the companies and a significant lag in some of the analyzed processes

ESTRATEGIA DE LOCALIZACIÓN CON ENFOQUE MULTIOBJETIVO PARA ALMACENES INTERMEDIOS EN PROCESOS DE RECICLAJE DE ENVASES DE VIDRIO

&lt;p class="MsoNormal" style="margin: 0in 0in 0pt; text-align: justify;"&gt;&lt;span style="font-size: 10pt;" lang="ES"&gt;&lt;span style="font-family: Times New Roman;"&gt;Los problemas de ubicación de instalaciones (&lt;em&gt;facilities location&lt;/em&gt;) son considerados por diversos autores, como problemas complejos o también llamados NP-&lt;em&gt;hard&lt;/em&gt;, y han sido ampliamente estudiados en literaturas especializadas de Investigación de Operaciones. La localización de instalaciones valora un conjunto de lugares factibles en los cuales pudieran situarse centros de producción de bienes, servicios, almacenes, etc. La ubicación de estas instalaciones implica costo de inversión en estructuras y otros costos asociados a la apertura de la misma, así como, una posible ganancia futura. A diferencia de otras investigaciones, el presente trabajo propone la obtención óptima de ubicación, con enfoque multiobjetivo, para varios almacenes simultáneamente, los cuales son declarados como intermedios en procesos de reciclaje de envases de vidrios para una cervecería cubana. El trabajo propone la utilización de Algoritmos Evolutivos Multiobjetivo, los cuales han sido abordados en investigaciones relacionadas con el tema pero orientados esencialmente a instalaciones de servicio.&lt;/span&gt;&lt;/span&gt;&lt;/p&gt

An alternative solution for the repair of electrical breakdowns after natural disasters based on ant colony optimization

Abundant literature is available for the route planning based on meta-heuristic algorithms. However, most researches in this field are developed under normal scenarios (e.g. normal weather conditions). The natural disasters, such as hurricanes, on the contrary, impose hard constraints to these combinatorial problems. In this paper, a route-planning problem is solved, specifically, for the repair of electrical breakdowns that occur after natural disasters. The problem is modeled using an assignment-based integer programming formulation proposed for the Multiple Traveling Salesman Problem (mTSP). Moreover, this paper proposes the creative application of an algorithm based on Ant Colony Optimization (ACO), specifically Multi-type Ant Colony System (M-ACS), where each colony represents a set of possible global solutions. Ants cooperate and compete by means of “frequent” pheromone exchanges aimed to find a solution. The algorithm performance has been compared against other ACO variant, showing the efficacy of the proposed algorithm on realistic decision-making.En la literatura especializada existe abundante literatura sobre la aplicación de meta-heurísticas en la planeación de rutas. Sin embargo, la mayoría de las investigaciones en este campo han sido desarrolladas bajo escenarios normales (ejemplo bajo condiciones meteorológicas normales). Los desastres naturales, por ejemplo los huracanes, incrementan la complejidad en este tipo de problemas combinatorios. En este artículo se resuelve un problema de planeación de ruta, específicamente para la reparación de averías eléctricas que suceden posteriores a un desastre natural. El problema es modelado empleando una formulación entera basada en asignación para Múltiples Viajeros Vendedores (mTSP). Por otra parte, en el artículo se propone una aplicación creativa de un algoritmo de optimización basado en Colonia de Hormigas (ACO), específicamente Sistema de Hormigas Multi-tipos, donde cada colonia representa un conjunto de posibles soluciones globales del problema. Las hormigas cooperan y compiten mediante frecuentes intercambios de feromonas para buscar una solución del problema. El desempeño del algoritmo ha sido comparado con otras variantes de ACO, mostrando la eficacia del algoritmo propuesto en ambiente realístico de la toma de decisiones

Heuristic for production scheduling on job-shop plants considering preventive maintenance tasks

The simultaneous analysis of production scheduling and preventive maintenance task attracts special attention of researchers due to its complexity and therefore the necessity to seek efficient methods for solving this kind of combinatorial problems. This paper presents a heuristic approach to solve this issue on job shop plants. The solution method includes a linear programming model, based on the Traveling Salesman Problem, where the setup time is considered as distance measure. The method ́s aim is to obtain a sequence of production orders and preventive maintenance tasks that reduce the idle time and the backlogs simultaneously, accomplishing the maintenance program. After finding an optimal solution for each machine a Correction Factor (CF) is determined as new distance measure. The CF considers the structure of the initial solution, the machine utilization and the product priorities. Then, the final solution is reached running the linear programming model using the distance updated values. Finally, the proposed heuristic is applied to real case study of the Cuban industry. The experimental results indicated a significant idle time reduction for the company under examination.El análisis simultáneo de la programación de la producción y las tareas de mantenimiento preventivo atrae especial atención en los investigadores debido a su gran complejidad y por ende la necesidad de encontrar métodos eficientes para resolver este tipo de problema combinatorio. Este artículo presenta un enfoque heurístico para resolver dicha problemática en plantas tipo job-shop. El método de solución incluye un modelo de programación lineal inspirado en el problema del Agente Vendedor, donde el tiempo de iniciación es considerado como métrica de distancia. El método persigue obtener una secuencia de las órdenes de producción y tareas de mantenimiento preventivo que reduzcan el tiempo ocioso y los retrasos simultáneamente, cumpliendo con el programa de mantenimiento. Luego de encontrar la solución óptima para cada máquina, un factor de corrección (CF) es determinado como la nueva medida de distancia. El factor CF considera la estructura inicial de solución, la utilización de las máquinas y las prioridades en los productos. De esta forma, la solución final es alcanzada solucionando el modelo de programación lineal usando los valores de distancia actualizados. Finalmente, la heurística propuesta es aplicada en un caso de estudio real de la Industria Cubana. Los resultados experimentales indicaron una reducción significativa del tiempo ocioso para la compañía objeto de estudio

Heuristic for production scheduling on job-shop plants considering preventive maintenance tasks

The simultaneous analysis of production scheduling and preventive maintenance task attracts special attention of researchers due to its complexity and therefore the necessity to seek efficient methods for solving this kind of combinatorial problems. This paper presents a heuristic approach to solve this issue on job shop plants. The solution method includes a linear programming model, based on the Traveling Salesman Problem, where the setup time is considered as distance measure. The method´s aim is to obtain a sequence of production orders and preventive maintenance tasks that reduce the idle time and the backlogs simultaneously, accomplishing the maintenance program. After finding an optimal solution for each machine a Correction Factor (CF) is determined as new distance measure. The CF considers the structure of the initial solution, the machine utilization and the product priorities. Then, the final solution is reached running the linear programming model using the distance updated values. Finally, the proposed heuristic is applied to real case study of the Cuban industry. The experimental results indicated a significant idle time reduction for the company under examination

Evaluación del desempeño ambiental bajo enfoque de cadena de abastecimiento verde

Entre los enfoques existentes de gestión ambiental, la gestión de cadenas de abastecimiento verde (Green Supply Chain Managemen t, GSCM), se ha convertido en uno de los más relevantes en los últimos años. El en foque GSCM aborda todos los procesos y actividad es que componen la cadena de abastecimiento en los eslabones de aprovi sionamiento, manufactura y entregas, incluyendo también el diseñ o, las compras, el marketing y la logística inve rsa. Aunque la revisión bibliográfica permiti ó identificar la existencia de una gran v ariedad de indicadores de desempeño ambiental que se enmarcan en el enfoque PresiónEstadoRes puesta, no se encontraron indicadores aplica dos bajo un enfoque GSCM. Por tanto, el presente ar tículo expone una metodología para la cons trucción de un indicador de corte multicrit erio que permite evaluar el desempeño ambiental desde el enfoque GSCM, con base en 8 procesos y 32 actividades detectadas en la revisión de literatura. El indicador fue aplicado en un grupo de 14 empresas de la región cafetera de Colombia. Los resultados indican un d esempeño heterogéneo entre las compañías analizadas y un rezago importante en algunos procesos

ASISTENCIA DECISIONAL EN EL PROCESO DE OPTIMIZACIÓN PARA EL ENRUTAMIENTO DE VEHÍCULOS

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&lt;w:LsdException Locked="false" Priority="32" SemiHidden="false" UnhideWhenUsed="false" QFormat="true" Name="Intense Reference" /&gt; &lt;w:LsdException Locked="false" Priority="33" SemiHidden="false" UnhideWhenUsed="false" QFormat="true" Name="Book Title" /&gt; &lt;w:LsdException Locked="false" Priority="37" Name="Bibliography" /&gt; &lt;w:LsdException Locked="false" Priority="39" QFormat="true" Name="TOC Heading" /&gt; &lt;/w:LatentStyles&gt; &lt;/xml&gt;&lt;![endif]--&gt;&lt;!--[if gte mso 10]&gt; &lt;mce:style&gt;&lt;! /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Tabla normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman","serif";} --&gt; &lt;!--[endif]--&gt;&lt;/p&gt;&lt;p class="MsoNormal" style="text-align: justify;"&gt;&lt;span style="font-size: 10pt;"&gt;El problema de enrutamiento de vehículos ha sido ampliamente estudiado por diferentes autores, generalmente especialistas en las áreas de la Investigación de Operaciones y la Logística. En ocasiones este problema se hace tan complejo que requiere algoritmos que encuentren su solución en tiempo factible y con adecuada calidad. Diversas investigaciones científicas han mostrado el uso efectivo de algoritmos heurísticos en problemas reales de enrutamiento de grandes dimensiones. Por otra parte, en un grupo no menos importante de investigaciones, se evidencian valiosas soluciones con algoritmos exactos y aproximados (los aproximados no serán abordados en esta investigación) aplicados a problemas de dimensiones inferiores. Es por ello que la motivación fundamental de esta investigación conduce a realizar un análisis previo a la optimización concreta de problemas reales de enrutamiento, con la finalidad de conocer en qué grupo de algoritmos (exactos o heurísticos) estará la posible solución de los mismos. En el trabajo se propone el uso de Análisis Discriminante, con vista a clasificar el área de solución para problemas reales de enrutamiento de vehículos en empresas cubanas.&lt;/span&gt;&lt;/p&gt; &lt;p class="MsoNormal" style="text-align: justify;"&gt; &lt;/p&gt; &lt;p class="MsoNormal" style="text-align: justify;"&gt;&lt;em&gt;&lt;span style="font-size: 10pt;" lang="EN-US"&gt;The Vehicle Routing Problem (VRP) has been extensively studied by different authors, often specialists in the areas of Operations Research and Logistics. Sometimes this problem is so complex that it requires algorithms to find feasible solution in time with adequate quality. Several researches have shown the effective use of heuristic algorithms on vehicle routing for large dimension problem.&lt;/span&gt;&lt;/em&gt;&lt;span class="longtext1"&gt;&lt;em&gt;&lt;span style="background: none repeat scroll 0% 0% white;" lang="EN-US"&gt; &lt;/span&gt;&lt;/em&gt;&lt;/span&gt;&lt;em&gt;&lt;span style="font-size: 10pt;" lang="EN-US"&gt;Moreover, in a not least important researches solutions are demonstrated with exact and approximate algorithms (the approximate not be addressed in this research) applied to problems with lower dimensions. For that reason the aim is to make an analysis before optimization process of real VRP in order to know which group of algorithms (exact or heuristic) will be the possible solution of them. The paper proposes &lt;a name="OLE_LINK25"&gt;&lt;/a&gt;&lt;a name="OLE_LINK24"&gt;&lt;span&gt;Discriminate Analysis&lt;/span&gt;&lt;/a&gt; in order to classify the solution area for a real VRP in Cuban Enterprise.&lt;/span&gt;&lt;/em&gt;&lt;/p&gt

Clustering Search and Variable Mesh Algorithms for continuous optimization

The hybridization of population-based meta-heuristics and local search strategies is an effective algorithmic proposal for solving complex continuous optimization problems. Such hybridization becomes much more effective when the local search heuristics are applied in the most promising areas of the solution space. This paper presents a hybrid method based on Clustering Search (CS) to solve continuous optimization problems. the CS divides the search space in clusters, which are composed of solutions generated by a population meta-heuristic, called Variable Mesh Optimization. Each cluster is explored further with local search procedures. Computational results considering a benchmark of multimodal continuous functions are presented. (C) 2014 Elsevier B.V. All rights reserved.Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Univ Manizales, Caldas, ColombiaUniv Cent Marta Abreu Las Villas, Santa Clara, CubaUniv Fed Maranhao, Sao Luis, MA, BrazilUniversidade Federal de São Paulo, São Paulo, BrazilInst Nacl Pesquisas Espaciais, Sao Jose Dos Campos, BrazilUniversidade Federal de São Paulo, ICT, São José dos Campos, BrazilCNPq: 300692/2009-9CNPq: 476862/2012-4Web of Scienc