Model Optimasi untuk Menentukan Tingkat Produksi Produk Multi Item Berkatagori Cepat Rusak

Tulisan ini berisi mengenai model optimasi  untuk menentukan tingkat produksi optimum bagi produk-produk berumur pendek atau produk katagori cepat rusak (perishable products). Pada tahun 2020 penulis telah mengembangkan model optimasi untuk menentukan tingkat produksi optimum untuk produk tunggal (single item) bagi produk katagori umur pendek atau cepat rusak (perishable products). Dalam tulisan ini penulis mengembangkan model tersebut untuk produk ganda atau multi produk (multi item). Variable biaya yang dipertimbangkan dalam model ini sama dengan model  single item yaitu diantaranya, biaya produksi, biaya set-up, biaya penyimpanan dan biaya kadaluarsa (expired cost). Model yang dikembangkan berangkat dari system produksi yang menganut system produksi batch (batch production system). Pada model multi item ini semua produk menggunakan fasilitas yang sama sehingga kegiatan produksi untuk tiap item dilakukan secara bergantian dengan mengikuti ukuran batch tertentu. Model optimasi yang dikembangkan adalah untuk menentukan ukuran batch setiap item dalam tiap putaran produksi sehingga dapat meminimasi biaya total, meminimasi kelangkaan serta mengurangi penumpukan yang berakibat terhadap terjadinya kadaluarsa. Konstrain yang dipertimbangkan adalah kapasitas, demand, dan life time (umur produk). Validasi model dilakukan secara matematis dan empiris. Secara matematis dilakukan dengan menggunakan konsep turunan, sedangkan empiris menggunakan contoh kasus ril di lapangan.Penulis  berharap model ini akan memberikan manfaat praktis bagi para praktisi maupun bagi kalangan akademisi khususnya mahasiswa.Tulisan ini berisi mengenai model optimasi  untuk menentukan tingkat produksi optimum bagi produk-produk berumur pendek atau produk katagori cepat rusak (perishable products). Pada tahun 2020 penulis telah mengembangkan model optimasi untuk menentukan tingkat produksi optimum untuk produk tunggal (single item) bagi produk katagori umur pendek atau cepat rusak (perishable products). Dalam tulisan ini penulis mengembangkan model tersebut untuk produk ganda atau multi produk (multi item). Variable biaya yang dipertimbangkan dalam model ini sama dengan model  single item yaitu diantaranya, biaya produksi, biaya set-up, biaya penyimpanan dan biaya kadaluarsa (expired cost). Model yang dikembangkan berangkat dari system produksi yang menganut system produksi batch (batch production system). Pada model multi item ini semua produk menggunakan fasilitas yang sama sehingga kegiatan produksi untuk tiap item dilakukan secara bergantian dengan mengikuti ukuran batch tertentu. Model optimasi yang dikembangkan adalah untuk menentukan ukuran batch setiap item dalam tiap putaran produksi sehingga dapat meminimasi biaya total, meminimasi kelangkaan serta mengurangi penumpukan yang berakibat terhadap terjadinya kadaluarsa. Konstrain yang dipertimbangkan adalah kapasitas, demand, dan life time (umur produk). Validasi model dilakukan secara matematis dan empiris. Secara matematis dilakukan dengan menggunakan konsep turunan, sedangkan empiris menggunakan contoh kasus ril di lapangan.Penulis  berharap model ini akan memberikan manfaat praktis bagi para praktisi maupun bagi kalangan akademisi khususnya mahasiswa

Integrated production-distribution scheduling with energy considerations for efficient food supply chains

Abstract Quantitative approaches for the integration of production and distribution planning are attracting the interest of scholars and companies in recent years. They can significantly improve supply chain performance and sustainability. In this paper, we propose an optimization model for the integrated scheduling of production and distribution activities, with reference to a real-life company in the food sector. The model takes into consideration changeover times and perishability, and aims to jointly minimize energy, storage and distribution costs. Its applicability is shown through a set of computational experiments, carried out on instances generated from historical data. Two different rescheduling strategies, where the first one reproduces the current behaviour of the firm, are compared. The results show that the current practices of the company can be improved and the model is a valid tool for supporting operational business decisions

A matheuristic approach combining genetic algorithm and mixed integer linear programming model for production and distribution planning in the supply chain

[EN] A number of research studies has addressed supply chain planning from various perspectives (strategical, tactical, operational) and demonstrated the advantages of integrating both production and distribution planning (PDP). The globalisation of supply chains and the fourth industrial revolution (Industry 4.0) mean that companies must be more agile and resilient to adapt to volatile demand, and to improve their relation with customers and suppliers. Hence the growing interest in coordinating production-distribution processes in supply chains. To deal with the new market¿s requirements and to adapt business processes to industry¿s regulations and changing conditions, more efforts should be made towards new methods that optimise PDP processes. This paper proposes a matheuristic approach for solving the PDP problem. Given the complexity of this problem, combining a genetic algorithm and a mixed integer linear programming model is proposed. The matheuristic algorithm was tested using the Coin-OR Branch & Cut open-source solver. The computational outcomes revealed that the presented matheuristic algorithm may be used to solve real sized problems.This work was supported by the Conselleria de Educación, Investigación, Cultura y Deporte - Generalitat Valenciana for hiring predoctoral research staff with Grant (ACIF/2018/170) and European Social Fund with Grant Operational Program of FSE 2014-2020, the Valencian Community. The research leading to these results received funding from the European Union H2020 Programme with grant agreement No. 958205 "Industrial Data Services for Quality Control in Smart Manufacturing" (i4Q) and the Regional Department of Innovation, Universities, Science and Digital Society of the Generalitat Valenciana entitled "Industrial Production and Logistics Optimization in Industry 4.0" (i4OPT) (Ref. PROMETEO/ 2021/065)Guzmán-Ortiz, BE.; Poler, R.; Andres, B. (2023). A matheuristic approach combining genetic algorithm and mixed integer linear programming model for production and distribution planning in the supply chain. Advances in Production Engineering & Management. 18(1):19-31. https://doi.org/10.14743/apem2023.1.454193118

Bütünleşik tedarik zinciri çizelgeleme modelleri: Bir literatür taraması

Research on integration of supply chain and scheduling is relatively recent, and number of studies on this topic is increasing. This study provides a comprehensive literature survey about Integrated Supply Chain Scheduling (ISCS) models to help identify deficiencies in this area. For this purpose, it is thought that this study will contribute in terms of guiding researchers working in this field. In this study, existing literature on ISCS problems are reviewed and summarized by introducing the new classification scheme. The studies were categorized by considering the features such as the number of customers (single or multiple), product lifespan (limited or unlimited), order sizes (equal or general), vehicle characteristics (limited/sufficient and homogeneous/heterogeneous), machine configurations and number of objective function (single or multi objective). In addition, properties of mathematical models applied for problems and solution approaches are also discussed.Bütünleşik Tedarik Zinciri Çizelgeleme (BTZÇ) üzerine yapılan araştırmalar nispeten yenidir ve bu konu üzerine yapılan çalışma sayısı artmaktadır. Bu çalışma, bu alandaki eksiklikleri tespit etmeye yardımcı olmak için BTZÇ modelleri hakkında kapsamlı bir literatür araştırması sunmaktadır. Bu amaçla, bu çalışmanın bu alanda çalışan araştırmacılara rehberlik etmesi açısından katkı sağlayacağı düşünülmektedir. Bu çalışmada, BTZÇ problemleri üzerine mevcut literatür gözden geçirilmiş ve yeni sınıflandırma şeması tanıtılarak çalışmalar özetlenmiştir. Çalışmalar; tek veya çoklu müşteri sayısı, sipariş büyüklüğü tipi (eşit veya genel), ürün ömrü (sınırlı veya sınırsız), araç karakteristikleri (sınırlı/yeterli ve homojen/heterojen), makine konfigürasyonları ve amaç fonksiyonu sayısı (tek veya çok amaçlı) gibi özellikler dikkate alınarak kategorize edildi. Ayrıca problemler için uygulanan matematiksel modellerin özellikleri ve çözüm yaklaşımları da tartışılmıştır

A Quick Response Algorithm for Dynamic Autonomous Mobile Robot Routing Problem with Time Windows

This paper investigates the optimization problem of scheduling autonomous mobile robots (AMRs) in hospital settings, considering dynamic requests with different priorities. The primary objective is to minimize the daily service cost by dynamically planning routes for the limited number of available AMRs. The total cost consists of AMR's purchase cost, transportation cost, delay penalty cost, and loss of denial of service. To address this problem, we have established a two-stage mathematical programming model. In the first stage, a tabu search algorithm is employed to plan prior routes for all known medical requests. The second stage involves planning for real-time received dynamic requests using the efficient insertion algorithm with decision rules, which enables quick response based on the time window and demand constraints of the dynamic requests. One of the main contributions of this study is to make resource allocation decisions based on the present number of service AMRs for dynamic requests with different priorities. Computational experiments using Lackner instances demonstrate the efficient insertion algorithm with decision rules is very fast and robust in solving the dynamic AMR routing problem with time windows and request priority. Additionally, we provide managerial insights concerning the AMR's safety stock settings, which can aid in decision-making processes

Optimizing Fresh Agricultural Product Distribution Paths Under Demand Uncertainty

Consumers' demand for fresh agricultural products (FAPs) and their quality requirements are increasing in the current agricultural-product consumption market. FAPs' unique perishability and short shelf-life features mean a high level of delivery efficiency is required to ensure their freshness and quality. However, consumers' demand for FAPs is contingent and geographically dispersed. Therefore, the conflicting relationship between the costs associated with the logistics distribution and the level of delivery quality is important to consider. In this paper, the authors consider a fresh agricultural-product distribution path planning problem with time windows (FAPDPPPTW). To address the FAPDPPPTW under demand uncertainty, a mixed-integer linear programming model based on robust optimization is proposed. Moreover, a particle swarm optimization algorithm combined with a variable neighborhood search is designed to solve the proposed mathematical model. The numerical experiment results show the robustness and fast convergence of the algorithm.</p

Medium-term optimization-based approach for the integration of production planning, scheduling and maintenance

A medium-term optimization-based approach is proposed for the integration of production planning, scheduling and maintenance. The problem presented in this work considers a multiproduct single-stage batch process plant with parallel units and limited resources. An MILP continuous-time formulation is developed based on the main ideas of travelling salesman problem and precedence-based constraints to deal with, sequence-dependent unit performance decay, flexible recovery operations, resource availability and product lifetime. Small scheduling examples have been solved and compared with adapted formulations from the literature, based on discrete-time and global-time events, demonstrating the effectiveness of the proposed solution approach. Additional planning and scheduling problems have been proposed by considering several time periods. Multi-period examples have been efficiently solved by the model showing the applicability of the solution approach for medium-size problems

Quality and Operations Management in Food Supply Chains: A Literature Review

We present a literature review on quality and operations management problems in food supply chains. In food industry, the quality of the food products declines over time and should be addressed in the supply chain operations management. Managing food supply chains with operations management methods not only generates economic benefit, but also contributes to environmental and social benefits. The literature on this topic has been burgeoning in the past few years. Since 2005, more than 100 articles have been published on this topic in major operations research and management science journals. In this literature review, we concentrate on the quantitative models in this research field and classify the related articles into four categories, that is, storage problems, distribution problems, marketing problems, and food traceability and safety problems. We hope that this review serves as a reference for interested researchers and a starting point for those who wish to explore it further

Integración de la producción y despachos en una planta de concreto.

En el siguiente trabajo de grado se presenta una propuesta para una integración de la producción y despechos en una empresa productora de concreto usando un método de programación entera mixta. Para esto se realiza una caracterización desde lo teórico y práctico en los procesos de programación de la producción y despachos del concreto premezclado, lo cual implica una búsqueda en el estado del arte del tema propuesto, por otra parte, se define los aspectos particulares como sus medidas de desempeño. Después se realiza la propuesta del modelo matemático con la literatura correspondiente y la selección del lenguaje donde se desarrolla, en este caso el solucionador AMPL, la finalidad del modelo es integrar la programación de la producción y despachos de tal manera que permita la optimización de la flota de vehículos. Por último, se valida el modelo matemático en el caso de estudio con su respectivo análisis de resultados, donde se definen escenarios de sensibilidad y también se realiza un análisis del impacto en el modelo de acuerdo con variaciones en los parámetros.PregradoINGENIERO(A) EN INDUSTRIA

A systematic literature review on machine learning applications for sustainable agriculture supply chain performance

Agriculture plays an important role in sustaining all human activities. Major challenges such as overpopulation, competition for resources poses a threat to the food security of the planet. In order to tackle the ever-increasing complex problems in agricultural production systems, advancements in smart farming and precision agriculture offers important tools to address agricultural sustainability challenges. Data analytics hold the key to ensure future food security, food safety, and ecological sustainability. Disruptive information and communication technologies such as machine learning, big data analytics, cloud computing, and blockchain can address several problems such as productivity and yield improvement, water conservation, ensuring soil and plant health, and enhance environmental stewardship. The current study presents a systematic review of machine learning (ML) applications in agricultural supply chains (ASCs). Ninety three research papers were reviewed based on the applications of different ML algorithms in different phases of the ASCs. The study highlights how ASCs can benefit from ML techniques and lead to ASC sustainability. Based on the study findings an ML applications framework for sustainable ASC is proposed. The framework identifies the role of ML algorithms in providing real-time analytic insights for pro-active data-driven decision-making in the ASCs and provides the researchers, practitioners, and policymakers with guidelines on the successful management of ASCs for improved agricultural productivity and sustainability