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نتیجه جستجو - Integer Linear Program

تعداد مقالات یافته شده: 78
ردیف عنوان نوع
1 Developing a two-stage model for a sustainable closed-loop supply chain with pricing and advertising decisions
در حال توسعه یک مدل دو مرحله ای برای یک زنجیره تامین حلقه بسته پایدار با تصمیمات قیمت گذاری و تبلیغات-2021
Closed-Loop Supply Chain (CLSC) has become a critical problem due to its effects on various factors including economic motivations, environmental concerns, and social impacts. Moreover, there are coordination tools, such as pricing and advertising, which impact its performance. In this paper, we offer a two-stage approach to model and solve a sustainable CLSC, taking into account pricing, green quality, and advertising. In the first stage, optimal decisions on pricing, greening, and advertising are made, while in the second stage, a fuzzy multi- objective Mixed Integer Linear Programming (MILP) model is used to maximize the total profit, reduce CO2 emissions, and improve social impacts. Suitable solution methods are introduced according to the scale of the problem. For small-scale instances, an augmented ϵ-constraint method is used to solve the problem. For large-scale instances, approximations are required, and a Lagrangian relaxation algorithm solves the problem in polynomial time. The performance of the proposed model is evaluated through various numerical examples. The results illustrate the applicability and efficiency of the model, while confirming significant improvements in sustainable objectives under optimal pricing, green quality, and advertising. Besides, the proposed Lagrangian relaxation method significantly reduces the computational time for large-scale instances, with only a 2.308% deviation from the optimal results.
Keywords: Sustainable closed-loop supply chain | Multi-objective programming | Supply chain pricing | Augmented ϵ-constraint | Lagrangian relaxation | CO2 emissions
مقاله انگلیسی
2 Efficient and sustainable closed-loop supply chain network design: A two-stage stochastic formulation with a hybrid solution methodology
طراحی شبکه زنجیره تامین حلقه بسته کارآمد و پایدار: یک فرمول تصادفی دو مرحله ای با روش راه حل ترکیبی-2021
In recent years, consumers and legislators have pushed companies to design their supply chain networks to consider environmental and social impacts as an important performance outcome. Due to the role of resource utilization as a key component of logistics network design, another primary goal of design is ensuring available scarce resources are used as efficiently as possible across all facilities. To address efficiency issues in a sustainable closed-loop supply chain network, a stochastic integrated multi-objective mixed integer nonlinear programming model is developed in this paper, in which sustainability outcomes as well as efficiency of facility resource utilization are considered in the design of a sustainable supply chain network. In doing so, efficiency is assessed using a bi-objective output-oriented data envelopment analysis model. A hybrid three-step solution methodology is presented that creates a linear form of the original mixed integer nonlinear programming problem using piecewise McCormick envelopes approach. In the second step, an aggregated single objective programming model is derived by exploiting the multi-choice goal programming. Finally, a Lagrangian relaxation algorithm is developed to effectively solve the latter stochastic single objective mixed integer linear programming problem. The application of the proposed approach is investigated with data drawn from a case study in the electronics industry. This case study illustrates how firms may balance sustainability and efficiency in the supply chain network design problem. Further, it demonstrates the integration of efficiency results in improving economic aspects of sustainability as well as social responsibility outcomes, but also highlights the trade-offs that exist between efficiency and environmental impacts.
Keywords: Closed-loop supply chain network | Sustainability | Data envelopment analysis | Stochastic programming | Multi-choice goal programming | Lagrangian relaxation
مقاله انگلیسی
3 A detailed MILP formulation for the optimal design of advanced biofuel supply chains
یک فرمول دقیق MILP برای طراحی بهینه زنجیره های پیشرفته تأمین سوخت زیستی-2021
The optimal design of a biomass supply chain is a complex problem, which must take into account multiple interrelated factors (i.e the spatial distribution of the network nodes, the efficient planning of logistics activities, etc.). Mixed Integer Linear Programming has proven to be an effective mathematical tool for the optimization of the design and the management strategy of Advanced Biofuel Supply Chains (ABSC). This work presents a MILP formulation of the economical optimization of ABSC design, comprising the definition of the associated weekly management plan. A general modeling approach is proposed with a network structure comprising two intermediate echelons (storage and conversion facilities) and accounts for train and truck freight transport. The model is declined for the case of a multi- feedstock ABSC for green methanol production tested on the Italian case study. Residual biomass feed- stocks considered are woodchips from primary forestry residues, grape pomace, and exhausted olive pomace. The calculated cost of methanol is equal to 418.7 V/t with conversion facility cost accounting for 50% of the fuel cost share while transportation and storage costs for around 15%. When considering only woodchips the price of methanol increases to 433.4 V/t outlining the advantages of multi-feedstock approach.© 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-NDlicense (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Keywords: Residual biomass | Advanced biofuels | Supply chain design | Logistics network | MILP | Optimization
مقاله انگلیسی
4 Bi-objective optimal design of hydrogen and methane supply chains based on Power-to-Gas systems
طراحی بهینه دو هدفه زنجیره های تأمین هیدروژن و متان بر اساس سیستم های نیرو به گاز-2021
This paper presents a methodological design framework for Hydrogen and Methane Supply Chains (HMSC) based on Power-to-Gas (PtG) systems. The novelty of the work is twofold, first considering a specific demand for hydrogen for electromobility in addition to the hydrogen demand required as a feedstock to produce synthetic methane from the methanation process. and performing a bi-objective optimization of the HMSC to provide effective support for the study of deployment scenarios. The approach is based on a Mixed Integer Linear Programming (MILP) approach with augmented epsilon-constraint implemented in the GAMS environment according to a multi-period approach (2035-2050) with several available energy sources (wind, PV, hydro, national network) for hydrogen production. Carbon dioxide sources stem mainly from mechanization and gasification processes. The objectives to be minimized simultaneously are the Total Annual Cost and the greenhouse gas emissions related to the whole HMSC over the entire period studied.
KEYWORDS: Power-to-Gas | Methanation | Hydrogen | MILP | Augmented epsilon constraint | GAMS | optimization approach
مقاله انگلیسی
5 A Novel Matheuristic based on bi-level optimization for the multi-Objective design of hydrogen supply chains
Matheuristic جدید مبتنی بر بهینه سازی سطح دو برای طراحی چند هدفه زنجیره های تأمین هیدروژن-2021
This work introduces an efficient tool for the design of sustainable hydrogen supply chains (HSCs), considering both economic and environmental concerns, through an appropriate multi-objective strategy. The original problem, being formulated as a bi-objective mixed-integer linear programming (MILP) problem, takes into consideration the availability of different energy sources, the installation and operation of hydrogen facilities of different sizes and technologies, and the transportation of hydrogen from production units to storage facilities. The area of study is divided into grids which have a specific hydrogen demand that evolves over time, thus a multi-period model of the HSC is considered. In order to overcome the computational burden associated to the solution of large size instances of the resulting problem, we proposed a solution strategy consisting of a hybrid algorithm. The original problem is reformulated into a bi-level optimization problem: the upper level (discrete problem) consists of finding the optimal location for production plants and storage facilities, whereas the lower level (continuous problem) minimizes their corresponding costs associated to transportation and facility operation. A multi-objective evolutionary algorithm is employed for the solution of the bi-objective upper level, whereas the bi-objective lower level is decomposed using a scalarizing function, which is then solved using a linear programming solver. The proposed methodology is validated through the comparison of the true Pareto fronts given by CPLEX with ε-constraint method, for six increasing size instances. Numerical results prove that the proposed hybrid approach produces an accurate approximation of the Pareto-optimal fronts, more efficiently than the exact solution approach.
مقاله انگلیسی
6 Designing and planning the downstream oil supply chain under uncertainty using a fuzzy programming approach
طراحی و برنامه ریزی زنجیره تأمین روغن پایین دستی تحت عدم اطمینان با استفاده از رویکرد برنامه نویسی فازی-2021
This paper addresses the strategic and tactical planning of a downstream oil supply chain (DOSC) subject to different sources of uncertainty. This problem is formulated as a mixed-integer linear programming (MILP) model, whereas uncertainty is tackled using chance constrained programming with fuzzy parameters. The MILP model aims at determining the network design and the products distribution plan in a cost-effective way. A real case study on the Brazilian oil industry is used to validate the model. The proposed model shows to be a valuable decision-support tool in order to aid the decision-making process in the strategic and tactical planning of real-life problems.
Keywords: Strategic and tactical planning | Downstream oil supply chain | Optimization | Fuzzy programming | Uncertainty
مقاله انگلیسی
7 A methodological design framework for hydrogen and methane supply chain with special focus on Power-to-Gas systems: application to Occitania region, France
یک چارچوب طراحی روش برای زنجیره تأمین هیدروژن و متان با تمرکز ویژه بر روی سیستم های نیرو به گاز: کاربرد در منطقه اوکسیتانیا ، فرانسه-2021
This work presents a methodological design framework for Hydrogen and Methane Supply Chains (HMSC). An innovative approach is to focus on Power-to-Hydrogen (PtH) and Power-to-Methane (PtM) concepts, and their interactions with other technologies, and energy carriers (i.e., Steam Methane Reforming – SMR, and natural gas). The overall objective of this work is to perform single objective and multi-objective optimizations for HMSC design to provide effective support for deployment scenarios. The methodological framework developed is based on a Mixed Integer Linear Programming (MILP) approach with augmented ε-constraint implemented in the GAMS environment according to a multi-period approach (2035-2050). Several available energy sources (wind, PV, hydro, national power grid, and natural gas) for hydrogen production through electrolysis and SMR are included. Carbon dioxide sources stem mainly from methanization and gasification processes, which are used to produce methane through methanation. The objective to be minimised in the single optimization approach is the total annual cost considering the externality of greenhouse gas emissions through the carbon price for the whole HMSC over the entire period studied. The multi-objective optimization includes as objectives the total annual cost, greenhouse gas emissions, and the total methane production from methanation. The Levelized Cost of Energy (LCOE), and the greenhouse gas emissions for each energy carrier are also computed. The results show that renewable hydrogen from PtG can be competitive with SMR through the implementation of carbon prices below 0.27 €/kgCO2. In the case of synthetic methane, the available resources can meet the demand through PtG, and even if synthetic methane for natural gas network injection is thus far from competitive with natural gas, power-to-gas technologies have the potential to decarbonize the fossil economy and achieve a circular economy through CO2 recovery.
KEYWORDS: Power-to-Gas | Methanation | Hydrogen | MILP | supply chain | optimization
مقاله انگلیسی
8 A supply chain disruption recovery strategy considering product change under COVID-19
یک استراتژی بازیابی اختلال در زنجیره تامین با توجه به تغییر محصول تحت COVID-19-2021
A recent global outbreak of Corona Virus Disease 2019 (COVID-19) has led to massive supply chain disruption, resulting in difficulties for manufacturers on recovering their supply chains in a short term. This paper presents a supply chain disruption recovery strategy with the motivation of changing the original product type to cope with that. In order to maximize the total profit from product changes, a mixed integer linear programming (MILP) model is developed with combining emergency procurement on the supply side and product changes by the manufacturer as well as backorder price compensation on the demand side. The model uses a heuristic algorithm based on ILOG CPLEX toolbox. Experimental results show that the proposed disruption recovery strategy can effectively reduce the profit loss of manufacturer due to late delivery and order cancellation. It is observed that the impact of supply chain disruptions is reduced. The proposed model can offer a potentially useful tool to help the manufacturers decide on the optimal recovery strategy whenever the supply chain system experiences a sudden massive disruption.
Keywords: Supply chain | Disruption | Recovery Plan | COVID-19 | Product change
مقاله انگلیسی
9 Impact of product perishability on agri-food supply chains design
تأثیر فسادپذیری محصول در طراحی زنجیره های تأمین مواد غذایی غذایی-2021
Perishability of agri-food products impacts the economic, environmental, and social aspects of agri-food supply chains (AFSCs). Product perishability is, usually, considered in tactical and operational decisions, but not in strategic ones, such as the design of the AFSC. The contribution of this paper is that it investigates the impact of product perishability on an AFSC design. To do so, first, a novel mixed-integer linear programming model is proposed to design entire AFSCs with multiple-products, which considers capacity, planting, harvesting, transporting and perishability constraints for a multiple-period horizon. A set of scenarios is generated by varying products’ shelf life and analysed. The results show that product perishability is relevant when designing AFSCs, especially for products with a short shelf life. The results show that an AFSC’s economic performance improves when product perishability is considered. The model can also help in determining the investment needed extend products shelf life while remaining profitable. Other uses could include tactical planning for chains already in place.
Keywords: Agri-food supply chain design | Planting | Harvest | Optimization | Shelf life
مقاله انگلیسی
10 Integrative design of the optimal biorefinery and bioethanol supply chain under the water-energy-food-land (WEFL) nexus framework
Integrative design of the optimal biorefinery and bioethanol supply chain under the water-energy-food-land (WEFL) nexus framework-2021
This study presents a comprehensive decision model for the integrative design of a biorefinery for bioethanol production and its supply chain (BPSC) under the water-energy-food-land (WEFL) nexus framework. A new optimization model was developed using a mixed integer linear programming to simultaneously identify the optimal process configuration of a bioethanol production plant and the optimal bioethanol supply network. The objective function of the model is to minimize the total annual cost for establishing and operating the BPSC to meet society’s needs (energy, water and food) under the limited resources and land availabilities, and technology capacity. The proposed model can provide the optimal solutions for design and operation of the BPSC: i) the types, and quantities of feedstocks; ii) types, number, and location of facilities and; iii) regional flows. The capability of the proposed model was validated through the case study of Jeju Island, Korea, with two scenarios: BPSC by cost (COPT) and nexus (NOPT) optimization. As a result, it was identified that the BPSC in NOPT requires higher energy supply cost (8.55 B$) than the COPT (6.44 B$). However, the BPSC in NOPT can satisfy the society demands with relatively smaller consumption of occupied land (2%), fresh water (30%) and primary energy consumption (64%) than that of the COPT, respectively.© 2021 Elsevier Ltd. All rights reserved.
Keywords: Nexus | Optimization | Biofuel | Bioethanol supply chain | Korea
مقاله انگلیسی
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