Decision support for build-to-order supply chain management through multiobjective optimization

This is the post-print version of the final paper published in International Journal of Production Economics. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2010 Elsevier B.V.This paper aims to identify the gaps in decision-making support based on multiobjective optimization (MOO) for build-to-order supply chain management (BTO-SCM). To this end, it reviews the literature available on modelling build-to-order supply chains (BTO-SC) with the focus on adopting MOO techniques as a decision support tool. The literature has been classified based on the nature of the decisions in different part of the supply chain, and the key decision areas across a typical BTO-SC are discussed in detail. Available software packages suitable for supporting decision making in BTO supply chains are also identified and their related solutions are outlined. The gap between the modelling and optimization techniques developed in the literature and the decision support needed in practice are highlighted. Future research directions to better exploit the decision support capabilities of MOO are proposed. These include: reformulation of the extant optimization models with a MOO perspective, development of decision supports for interfaces not involving manufacturers, development of scenarios around service-based objectives, development of efficient solution tools, considering the interests of each supply chain party as a separate objective to account for fair treatment of their requirements, and applying the existing methodologies on real-life data sets.Brunel Research Initiative and Enterprise Fund (BRIEF

Supply chain planning in the food industry : a systematic literature review

PURPOSE: Advanced Planning Systems (APS) can contribute to improved decision making and enhanced efficiency along complex food supply chains. This paper presents a systematic literature review of supply chain planning (SCP) in the food industry. In particular, the literature on three increasingly important planning tasks supported by APS is examined, namely Supply Chain Network Design, Sales & Operations Planning and Production Planning & Scheduling. METHODOLOGY: A literature review is conducted by systematically collecting the existing literature published between 1998 and 2020 and classifying it based on three planning tasks supported by APS modules (Supply Chain Network Design, Sales & Operations Planning and Production Planning & Scheduling). Furthermore, research papers are categorized according to the product under consideration, geographic region and method. FINDINGS: Multiple models for SCP practices have been developed. The modelling literature is fragmented around specific challenges faced in food supply chains. Empirical literature including case studies on the implementation of APS is sparse. The findings suggest that developed models for the three examined planning tasks are only implemented to a limited extent in practice. ORIGINALITY: This paper focuses on three planning tasks that are of increasing relevance for the food industry. The literature review can help practitioners within the food industry to get insights regarding the opportunities offered by the three software modules examined in this paper. Further research should be conducted in these areas to make literature on SCP more practically relevant for managers

Models and Algorithms for Production Planning and Scheduling in Foundries – Current State and Development Perspectives

Mathematical programming, constraint programming and computational intelligence techniques, presented in the literature in the field of operations research and production management, are generally inadequate for planning real-life production process. These methods are in fact dedicated to solving the standard problems such as shop floor scheduling or lot-sizing, or their simple combinations such as scheduling with batching. Whereas many real-world production planning problems require the simultaneous solution of several problems (in addition to task scheduling and lot-sizing, the problems such as cutting, workforce scheduling, packing and transport issues), including the problems that are difficult to structure. The article presents examples and classification of production planning and scheduling systems in the foundry industry described in the literature, and also outlines the possible development directions of models and algorithms used in such systems

Mathematics in the Supply Chain

[no abstract available

Decision support for build-to-order supply chain management through multiobjective optimization

This paper aims to identify the gaps in decision-making support based on multiobjective optimization for build-to-order supply chain management (BTOSCM). To this end, it reviews the literature available on modelling build-to-order supply chains (BTO-SC) with the focus on adopting multiobjective optimization (MOO) techniques as a decision support tool. The literature has been classified based on the nature of the decisions in different part of the supply chain, and the key decision areas across a typical BTO-SC are discussed in detail. Available software packages suitable for supporting decision making in BTO supply chains are also identified and their related solutions are outlined. The gap between the modelling and optimization techniques developed in the literature and the decision support needed in practice are highlighted and future research directions to better exploit the decision support capabilities of MOO are proposed

Methods and algorithms for integrated multi-scale optimisation of production planning and scheduling

Imperial Users onl

A Parallelizable Heuristic for Solving the Generic Materials and Operations Planning in a Supply Chain Network: A Case Study from the Automotive Industry

[EN] A trend in up-to date developments in multi-site operations planning models is to consider in details the different ways to produce, buy or transport products and the distributed decision-making process for operations planning. One of the most generic approaches to support global optimization in those supply chain networks by considering all the different operations alternatives and product structures is the Generic Materials & Operations Planning Problem. This problem can be modelled by a Mixed Integer Linear Programming model capable of considering production, transportation, procurement tasks and their alternatives and other relevant issues such as packaging. The aim of this paper is to introduce the implementation of a parallelizable heuristic method for materials and operations planning and its application to a case of a Supply Chain Network of the automotive industry. The approach uses variants of the GMOP model to overcome traditional MRP systems' limitations.Maheut ., JP.; García Sabater, JP. (2013). A Parallelizable Heuristic for Solving the Generic Materials and Operations Planning in a Supply Chain Network: A Case Study from the Automotive Industry. IFIP Advances in Information and Communication Technology. 397:151-157. doi:10.1007/978-3-642-40352-1_20S151157397Maheut, J., Garcia-Sabater, J.P.: La Matriz de Operaciones y Materiales y la Matriz de Operaciones y Recursos, un nuevo enfoque para resolver el problema GMOP basado en el concepto del Stroke. Dirección y Organización 45, 46–57 (2011)Garcia-Sabater, J.P., Maheut, J., Marin-Garcia, J.A.: A new formulation technique to model Materials and Operations Planning: the Generic Materials and Operations Planning (GMOP) Problem. European J. Industrial Engineering 7, 119–147 (2013)Mula, J., Maheut, J., Garcia-Sabater, J.P.: Supply Chain Network Design. Journal of Marketing and Operations Management Research 1, 378–383 (2012)Dudek, G., Stadtler, H.: Negotiation-based collaborative planning between supply chains partners. European Journal of Operational Research 163, 668–687 (2005)Torabi, S.A., Hassini, E.: Multi-site production planning integrating procurement and distribution plans in multi-echelon supply chains: an interactive fuzzy goal programming approach. International Journal of Production Research 47, 5475–5499 (2009)Kanyalkar, A.P., Adil, G.K.: Aggregate and detailed production planning integrating procurement and distribution plans in a multi-site environment. International Journal of Production Research 45, 5329–5353 (2007)de Kok, T.G., Fransoo, J.C.: Planning Supply Chain Operations: Definition and Comparison of Planning Concepts. In: Graves, S.C. (ed.) Handbooks in Operations Research and Management Science Supply Chain Management: Design, Coordination and Operation, vol. 11, pp. 597–675. Elsevier (2003)Buschkühl, L., Sahling, F., Helber, S., Tempelmeier, H.: Dynamic capacitated lot-sizing problems: a classification and review of solution approaches. OR Spectrum (2009)Maheut, J., Garcia-Sabater, J.P., Mula, J.: A supply Chain Operations Lot-Sizing and Scheduling Model with Alternative Operations. In: Sethi, S.P., Bogataj, M., Ros-McDonnell, L. (eds.) Proceedings of the Industrial Engineering: Innovative Networks, 5th International Conference on Industrial Engineering and Industrial Management "CIO 2011", Cartagena, Spain, pp. 309–316. Springer, London (2012)Garcia-Sabater, J.P., Maheut, J., Garcia-Sabater, J.J.: A two-stage sequential planning scheme for integrated operations planning and scheduling system using MILP: the case of an engine assembler. Flexible Services and Manufacturing Journal 24, 171–209 (2012)Pinto, J.M., Chen, P., Papageorgiou, L.G.: A discrete/continuous time MILP model for medium term planning of single stage multiproduct plants, pp. 1–6. Elsevier, B.V. (2007)Scheer, A.W.: Business Process Engineering - Reference Models for Industrial Enterprises. Springer (1994)Lin, J.T., Chen, T.L., Lin, Y.T.: Critical material planning for TFT-LCD production industry. International Journal of Production Economics 122, 639–655 (2009)Escudero, L.F.: CMIT, capacitated multi-level implosion tool. European Journal of Operational Research 76, 511–528 (1994)Maheut, J., Garcia-Sabater, J.P., Valero-Herrero, M.: MILP model for solving the supply chain operations scheduling problem with alternative operations considering delay penalization: a case study of a mass customization company. In: Proceedings of the 41st International Conference on Computers & Industrial Engineering, pp. 289–294 (2011

When do I want to know and why? Different demands on sugarcane yield predictions

FAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOThe production planning processes of sugarcane mills require quantitative information to support decisions on sugarcane yield and the effects of decisions made during planning. An exploratory study was conducted at a sugarcane mill with the goals of identifying the main decisions influenced by the prospects of future yield and of evaluating the manner in which those forecasts affect planning. Key decisions and their characteristics were identified based on a series of interviews and activity monitoring. These decisions are presented and discussed in relation to various solutions proposed by the scientific community for planning, as well as within the concept of Advanced Planning Systems. The yield forecasts used to inform budgeting and harvesting plans are of critical importance because actions taken based on those forecasts affect the entire value chain, highlighting the need for a decision-making framework that assess the effects of decisions on subsequent processes. Advanced Planning Systems design to the sugar value chain should incorporate the use of yield forecasts for production and must address the uncertainties throughout the entire system. These improvements can enhance the performances of Advanced Planning Systems by producing an integrated planning approach that is based on a comprehensive assessment of the sugar value chain. (C) 2014 Elsevier Ltd. All rights reserved.The production planning processes of sugarcane mills require quantitative information to support decisions on sugarcane yield and the effects of decisions made during planning. An exploratory study was conducted at a sugarcane mill with the goals of ident1354856FAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOFAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOFAPESP [12/50049-3]12/50049-