2,303 research outputs found

    Integrated management of hierarchical levels: towards a CAPE tool

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    The integration of decision-making procedures usually assigned to different hierarchical production systems requires the use of complex mathematical models and high computational efforts, in addition to the need of an extensive management of data and knowledge within the production systems. This work addresses this integration problem and proposes a comprehensive solution approach, as well as guidelines for Computer Aided Process Engineering (CAPE) tools managing the corresponding cyberinfrastructure. This study presents a methodology based on a domain ontology which is used as the connector between the introduced data, the different available formulations developed to solve the decision-making problem, and the necessary information to build the finally required problem instance. The methodology has demonstrated its capability to help exploiting different available decision-making problem formulations in complex cases, leading to new applications and/or extensions of these available formulations in a robust and flexible way.Peer ReviewedPostprint (author's final draft

    Tedarik zinciri optimizasyon çalışmaları: Literatür araştırması ve sınıflama

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    Supply chain planning is an integrated process in which a group of several organizations, such as suppliers, producers, distributors and retailers, work together. It comprises procurement, production, distribution and demand planning topics. These topics require taking strategical, tactical and operational decisions. This research aims to reveal which supply chain topics, which decision levels, and which optimization methods are mostly studied in supply chain planning. This paper presents a total of 77 reviewed works published between 1993 and 2016 about supply chain planning. The reviewed works are categorized according to following elements: decision levels, supply chain optimization topics, objectives, optimization models.Tedarik Zinciri, tedarikçiler, üreticiler, dağıtıcılar ve toptancılar gibi bir grup organizasyonu birleştiren entegre bir süreçtir. Tedarik, üretim, dağıtım ve talep planlama konularını içerir. Bu konular stratejik, taktik ve operasyonel kararlar almayı gerektirir. Bu araştırma tedarik zinciri planlamasında hangi tedarik zinciri konularının, hangi karar/planlama seviyelerinin ve hangi optimizasyon metotlarının literatürde en çok çalışıldığını göstermektedir. Çalışma 1993 ve 2016 yılları arasındaki tedarik zinciri planlama konusundaki 77 adet çalışmanın incelenmesine ait sonuçları sunmaktadır. İncelenen çalışmalar şu kriterlere gore kategorize edilmiştir: karar seviyesi, tedarik zinciri optimizasyon konuları, amaçlar, optimizasyon modelleri

    A review of discrete-time optimization models for tactical production planning

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    This is an Accepted Manuscript of an article published in International Journal of Production Research on 27 Mar 2014, available online: http://doi.org/10.1080/00207543.2014.899721[EN] This study presents a review of optimization models for tactical production planning. The objective of this research is to identify streams and future research directions in this field based on the different classification criteria proposed. The major findings indicate that: (1) the most popular production-planning area is master production scheduling with a big-bucket time-type period; (2) most of the considered limited resources correspond to productive resources and, to a lesser extent, to inventory capacities; (3) the consideration of backlogs, set-up times, parallel machines, overtime capacities and network-type multisite configuration stand out in terms of extensions; (4) the most widely used modelling approach is linear/integer/mixed integer linear programming solved with exact algorithms, such as branch-and-bound, in commercial MIP solvers; (5) CPLEX, C and its variants and Lindo/Lingo are the most popular development tools among solvers, programming languages and modelling languages, respectively; (6) most works perform numerical experiments with random created instances, while a small number of works were validated by real-world data from industrial firms, of which the most popular are sawmills, wood and furniture, automobile and semiconductors and electronic devices.This study has been funded by the Universitat Politècnica de València projects: ‘Material Requirement Planning Fourth Generation (MRPIV)’ (Ref. PAID-05-12) and ‘Quantitative Models for the Design of Socially Responsible Supply Chains under Uncertainty Conditions. Application of Solution Strategies based on Hybrid Metaheuristics’ (PAID-06-12).Díaz-Madroñero Boluda, FM.; Mula, J.; Peidro Payá, D. (2014). A review of discrete-time optimization models for tactical production planning. International Journal of Production Research. 52(17):5171-5205. doi:10.1080/00207543.2014.899721S51715205521

    Supply Chain Optimization Studies: A Literature Review and Classification

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    Supply chain planning is an integrated process in which a group of several organizations, such as suppliers, producers, distributors and retailers, work together. It comprises procurement, production, distribution and demand planning topics. These topics require taking strategical, tactical and operational decisions. This research aims to reveal which supply chain topics, which decision levels, and which optimization methods are mostly studied in supply chain planning. This paper presents a total of 77 reviewed works published between 1993 and 2016 about supply chain planning. The reviewed works are categorized according to following elements: decision levels, supply chain optimization topics, objectives, optimization models. 

    Supply Chain Optimization Studies: A Literature Review and Classification

    Get PDF
    Supply chain planning is an integrated process in which a group of several organizations, such as suppliers, producers, distributors and retailers, work together. It comprises procurement, production, distribution and demand planning topics. These topics require taking strategical, tactical and operational decisions. This research aims to reveal which supply chain topics, which decision levels, and which optimization methods are mostly studied in supply chain planning. This paper presents a total of 77 reviewed works published between 1993 and 2016 about supply chain planning. The reviewed works are categorized according to following elements: decision levels, supply chain optimization topics, objectives, optimization models. 

    Real-time optimization of an integrated production-inventory-distribution problem.

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    In today\u27s competitive business environment, companies face enormous pressure and must continuously search for ways to design new products, manufacture and distribute them in an efficient and effective fashion. After years of focusing on reduction in production and operation costs, companies are beginning to look into distribution activities as the last frontier for cost reduction. In addition, an increasing number of companies, large and small, are focusing their efforts on their core competencies which are critical to survive. This results in a widespread practice in industry that companies outsource one or more than one logistics functions to third party logistics providers. By using such logistics expertise, they can obtain a competitive advantage both in cost and time efficiency, because the third party logistics companies already have the equipment, system and experience and are ready to help to their best efforts. In this dissertation, we developed an integrated optimization model of production, inventory and distribution with the goal to coordinate important and interrelated decisions related to production schedules, inventory policy and truckload allocation. Because outsourcing logistics functions to third party logistics providers is becoming critical for a company to remain competitive in the market place; we also included an important decision of selecting carriers with finite truckload and drivers for both inbound and outbound shipments in the model. The integrated model is solved by modified Benders decomposition which solves the master problem by a genetic algorithm. Computational results on test problems of various sizes are provided to show the effectiveness of the proposed solution methodology. We also apply this proposed algorithm on a real distribution problem faced by a large national manufacturer and distributor. It shows that such a complex distribution network with 22 plants, 7 distribution centers, 8 customer zones, 9 products, 16 inbound and 16 outbound shipment carriers in a 12-month planning period can be redesigned within 33 hours. In recent years, multi-agent simulation has been a preferred approach to solve logistics and distribution problems, since these problems are autonomous, distributive, complex, heterogeneous and decentralized in nature and they require extensive intelligent decision making. Another important part in this dissertation involved a development of an agent-based simulation model to cooperate with the optimal solution given by the optimization model. More specifically, the solution given by the optimization model can be inputted as the initial condition of the agent-based simulation model. The agent-based simulation model can incorporate many other factors to be considered in the real world, but optimization cannot handle these as needed. The agent-based simulation model can also incorporate some dynamics we may encounter in the real operations, and it can react to these dynamics in real time. Various types of entities in the entire distribution system can be modeled as intelligent agents, such as suppliers, carriers and customers. In order to build the simulation model more realistic, a sealed bid multiunit auction with an introduction of three parameters a, ß and y is well designed. With the help of these three parameters, each agent makes a better decision in a simple and fast manner, which is the key to realizing real-time decision making. After building such a multi-agent system with agent-based simulation approach, it supports more flexible and comprehensive modeling capabilities which are difficult to realize in a general optimization model. The simulation model is tested and validated on an industrial-sized problem. Numerical results of the agent-based simulation model suggest that with appropriate setting of three parameters the model can precisely represent the preference and interest of different decision makers

    An Integrated Strategy for a Production Planning and Warehouse Layout Problem: Modeling and Solution Approaches

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    We study a real-world production warehousing case, where the company always faces the challenge to find available space for their products and to manage the items in the warehouse. To resolve the problem, an integrated strategy that combines warehouse layout with the capacitated lot-sizing problem is presented, which have been traditionally treated separately in the existing literature. We develop a mixed integer linear programming model to formulate the integrated optimization problem with the objective of minimizing the total cost of production and warehouse operations. The problem with real data is a large-scale instance that is beyond the capability of optimization solvers. A novel Lagrangian relax-and-fix heuristic approach and its variants are proposed to solve the large-scale problem. The preliminary numerical results from the heuristic approaches are reported
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