Hierarchical planning approach for a production- distribution system (original) (raw)
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A PROPOSED MODEL FOR INTEGRATED PRODUCTION-DISTRIBUTION PLANNING
The 19th International Conference on Management of Technology, IAMOT 2010, 2010
Getting products to customers faster and more reliably than competitors has become a requirement rather than a competitive advantage. In the last decade many companies have recognized that important cost savings and improved service levels can be achieved by effectively integrating production plans, inventory control and transportation policies throughout their supply chains. The focus is on planning models that integrate decisions across the supply chain. Achieving a level of integration that will yield new benefits requires that the production and distribution decisions be made in an integrated and optimized framework. In this paper, integrated multi-commodity production and distribution planning model has been developed. A proposed Mixed Integer Programming (MIP) model was developed with the objective of producing an optimum integrated production and distribution plan. The model considers the number of products to be produced and distributed in the different planning periods. It takes into account the production capacity, the vehicles capacity, the demand of each product, and the total costs associated with production, inventory, and transportation. The model was tested and verified with reference to a benchmark case. LINGO ® optimization package was used successfully in implementing and solving the model. The model is intended to improve the decision making process in terms of quality and speed of decision making.
Coordination of production and distribution planning
European Journal of Operational Research, 1994
This paper is a computational study to investigate the value of coordinating production and distribution planning. The particular scenario we consider concerns a plant that produces a number of products over time and maintains an inventory of finished goods at the plant. The products are distributed by a fleet of trucks to a number of retail outlets at which the demand for each product is known for every period of a planning horizon. We compare two approaches to managing this operation, one in which the production scheduling and vehicle routing problems are solved separately, and another in which they are coordinated within a single model. The two approaches are applied to 132 distinct test cases with different values of the basic model parameters, which include the length of the planning horizon, the number of products and retail outlets, and the cost of setups, inventory holding and vehicle travel. The reduction in total operating cost from coordination ranged from 3% to 20%. These results indicate the conditions under which companies should consider the organizational changes necessary to support coordination of production and distribution.
Models and algorithms for integrated production and distribution problems
Computers & Industrial Engineering, 2021
Motivated by real-world applications from the non-perishable food and beverage industry, we consider a general optimization problem that involves production, distribution and warehouse logistics. The problem deals with the logistic network design and material flow management to supply the multi-product and multi-period customer demand. Decisions on production site use, including lot-sizing, setup and minimum batches are taken from a cost saving perspective together with warehouse management decisions, including shipments to external warehouses. We present a mathematical formulation of the problem that is based on a Mixed Integer Linear Programming (MILP) model and takes into account all the nasty constraints that are present in the real problem. We show that such a model is computationally hard even using a state-of-the-art commercial solver, and introduce a metaheuristic algorithm that we use to compute approximate solutions. We test the proposed algorithms on two realworld test-cases and on a large set of realistic problems. The results show that, in all cases, the algorithm is very fast and produces solutions whose quality is very close to those that can be obtained by running a state-of-the-art commercial solver on the mathematical model for a very long time, thus providing for an efficient method for evaluating effective policies to be used under different scenarios. The models and the solving algorithms are of help to the industrial practitioners for the mid-term tactical management of their logistic networks.
Hierarchical Planning Methodology for a Supply Chain Management
Hierarchical production planning is a widely utilized methodology for real world capacitated production planning systems with the aim of establishing different decision–making levels of the planning issues on the time horizon considered. This paper presents a hierarchical approach proposed to FER CREACIONES Ltd., a company that produces reusable shopping bags in Chile and Perú, to determine the optimal allocation of resources at the tactical level as well as over the most immediate planning horizon to meet customer demands for the next weeks. Starting from an aggregated production planning model, the aggregated decisions are disaggregated into refined decisions in two levels, using a couple of optimization models that impose appropriate constraints to keep coherence of the plan on the production system. The main features of the hierarchical solution approach are presented.
Research Article, 2020
In this study, we propose to solve a biobjective tactical integrated production-distribution planning problem for a multisite, multiperiod, multiproduct, sea-air intermodal supply chain network under uncertainties. Two random parameters are considered simultaneously: product replenishment orders and production capacity, which are modelled via a finite set of scenarios, using a two-stage stochastic approach. A corresponding mathematical model is developed, coded, and solved using the LINGO 18.0 software optimisation tool. is model aims to simultaneously minimise the total costs of production in both regular and overtime, inventory, distribution, and backordering activities and maximise the customer satisfaction level over the tactical planning horizon. e AUGMECON technique is applied to handle with the multiobjective optimisation. e applicability and the performance of the proposed model are tested through a real-life case study inspired from a medium-sized Tunisian textile and apparel company. Sensitivity analysis on stochastic parameters and managerial insights for the studied supply chain network are argued based on the empirical findings.
Hierarchical production planning and multi-echelon inventory management
International Journal of Production Economics, 1992
In this paper we present a framework for the planning and control of the materials flow in a multi-item production system. Our prime objective is to meet a prespecitied customer service level at minimum overall costs. In order to motivate our study we first outline the basic architecture of a logistic control system developed at Philips Electronics. Guided by this exposure, we next describe the basic algorithmic framework which is needed to turn the conceptual ideas into operational procedures. The theory is extended with hierarchical planning procedures recognizing the need to first plan on a product family Ieve before disaggregating into plans for end-items.
The Design of Production-Distribution Networks: A Mathematical Programming Approach
This text proposes a mathematical programming approach to design international production-distribution networks for make-to-stock products with convergent manufacturing processes. Various formulations of the elements of production-distribution network design models are discussed. The emphasis is put on modeling issues encountered in practice which have a significant impact on the quality of the logistics network designed. The elements discussed include the choice of an objective function, the definition of the planning horizon, the manufacturing process and product structures, the logistics network structure, demand and service requirements, facility layouts and capacity options, product flows and inventory modeling, as well as financial flows modeling. Major contributions from the literature are reviewed and a number of new formulation elements are introduced. A typical model is presented, and the use of successive mixed-integer programming to solve it with commercial solvers is discussed. A more general version of the model presented and the solution method described were implemented in a commercial supply chain design tool which is now available on the market.