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Sustainable supply chain management for perishable products in emerging markets: An integrated location-inventory-routing model
مدیریت پایدار زنجیره تأمین برای محصولات فاسدشدنی در بازارهای نوظهور: یک مدل مسیریابی-موجودی-مکانیابی یکپارچه-2021 The demand for perishable products in emerging markets has been increasing. However, the perishability of products brings tremendous challenges for firms to build a sustainable supply chain. In this paper, we propose an integrated model of location-inventory-routing for perishable products, considering the factors of carbon emissions and product freshness. First, the economic cost, carbon emission levels, and freshness of the perishable products are analyzed. Second, with the goals of achieving the lowest economic cost and carbon emissions and the highest product freshness, a multi-objective planning model is developed, and constraints are established based on the actual location-inventory-routing situation. Third, the YALMIP toolbox is used to solve the model, and the optimal solution to this complex multi-objective problem is obtained. Finally, the effectiveness and feasibility of the proposed method are verified by the case study, as well as the sensitivity vehicle speed to the results. It is found that the integrated model proposed in this paper is able to significantly improve the efficiency of perishable goods supply chain management from the perspective of global optimization, and vehicle speed is able to significantly affect economic costs and carbon emissions. Keywords: Emerging market | Sustainable operations | Perishable product supply chain | Location-inventory-routing integration | Carbon emissions |
مقاله انگلیسی |
2 |
A Multi-Objective Green Hub Location Problem with Multi Item-Multi Temperature Joint Distribution for Perishable Products in Cold Supply Chain
یک مشکل مکان یابی Green Hub چند هدفه با توزیع مشترک چند ماده ای - چند دما برای محصولات فاسدشدنی در زنجیره تامین سرد-2021 This paper investigates a bi-objective green hub location problem, in which multiple perishable products with various storage temperatures can be distributed simultaneously in a cold supply chain (CSC).
The objectives of this problem include minimizing the system’s total cost (including transportation, hub
establishment, adjustment of the storage compartments’ temperatures, and carbon emission costs) and
maximizing the quality of the delivered product to the customer via the proposed model. Mixed-integer
linear programming (MILP) in the GAMS software was employed to formulate this problem. Then, the
ε-Constraint method was adopted to solve the presented bi-objective model to obtain the Pareto frontier
and consequently, a numerical example based on the CAB (Civil Aeronautics Board) database is presented
to validate the applicability of the model. The solutions of the model provide information regarding the
hub location (HL), allocating customers to the hubs, allocating customers to the vehicles, and the sequence of vehicles’ services for the Multi Item-Multi Temperature Joint Distribution of perishable products in CSCs. Moreover, the final results revealed the existence of a contradictory exchange between the
two objectives of this paper, implying that the higher is the quality of the delivered perishable product to
the customer, the greater is the system’s total cost. The novelty of the proposed model compared to other
hub location problems (HLPs) lies in the integration of the tactical/operational decisions with strategic
decisions to provide logistic solutions in CSCs by considering the carbon emissions as an environmental
factor in the transportation systems for the simultaneous distribution of dissimilar storage temperatures
perishable products within a CSC. The proposed model in this research can help the distributers of perishable products by maintaining the quality of the delivered items and reducing the system’s total costs
and considering the carbon emissions of transportation systems. This study has practical implications
for the logistics and CSCs managers to not only establish a distribution network for multiple perishable
products on the basis of the findings, but also respond to the environmental sustainability. Keywords: Hub Location | Perishable Products | Cold Supply Chain | Transportation | Multi-objective |
مقاله انگلیسی |
3 |
Sustainable and resilience planning for the supply chain of online hyperlocal grocery services
برنامه ریزی پایدار و انعطاف پذیر برای زنجیره تأمین خدمات مواد غذایی آنلاین بیش از حد محلی-2021 In an uncertain Supply Chain (SC) environment dealing with suppliers and transport-level
disruptions in addition to fulfilling customers’ requirements is a complex task. Such
challenges are more taxing in case of perishable products SCs. The concurrent effect of all
such events affects the economic stability of SC and impedes sustainability on a longer
planning horizon. The proposed study presents a case example of e-commerce based SC
addressing an operational and distribution planning problem. For this purpose, the study
simulates online grocery business operations by proposing a mixed-integer linear
programming problem to minimize SCs expected cost. It includes the costs of purchase,
transportation, supply-demand mismatch, and cost of economic loss due to the perishable
nature of the products. Computational analysis is performed to manifest the performance of
the proposed model considering the dataset of a hyperlocal distribution service. The study
evaluates the utility of resilience and sustainable strategies to minimize expected economic
costs and reduce environmental impacts by effectively managing waste. A backup strategy is
devised to promote a resilient SC planning to fight the risk of disruptions and operational
failures. Additionally, economic sustainability is achieved by implementing various
markdown policies and waste minimization strategies. A sensitivity analysis using MonteCarlo simulation is presented to recognize the impact of operational risk, demand uncertainty,
and perishability on the expected cost. Majorly, it contributes to the scant literature of
quantitative modeling for the production and distribution of food SC to promote resiliently
sustainable planning. Further, the resilient and sustainable strategies, procurement policies,
penalty assessment, and markdown due to perishability are some of the key contributions of
the study. The discussion provides plenty of opportunities to pursue future studies in
operational and distribution management of e-commerce SCs.
Keywords: supply chain | hyperlocal grocery business | perishable food | resilient policy | sustainability | uncertainty |
مقاله انگلیسی |
4 |
An efficient optimization framework for tracking multiple quality attributes in supply chains of perishable products
یک چارچوب بهینه سازی کارآمد برای ردیابی چندین ویژگی کیفی در زنجیره های تأمین محصولات فاسدشدنی-2021 Improved supply chain optimization strategies can play a major role in addressing global food security
and safety in years to come. In particular, tighter safety regulations, changing consumer quality requirements and more stringent market competition call upon integrated supply chain decision-making frameworks that explicitly consider product quality control. This effort requires metrics of quality that accurately reflect product physico-chemical properties, as well as consumer purchasing preferences. However,
a critical challenge linked to embedding the complex dynamics of the evolution of product quality in time
within supply chain models is the large-scale nature of the ensuing optimization problems, which are
computationally intractable even for moderate-size, single-item systems. In the present work, we introduce a computationally efficient optimal production and distribution planning framework for perishable
products having multiple quality attributes that evolve in time as a function of environmental conditions
during shipment and storage. We also propose a model reduction strategy and a decomposition framework that enhance the scalability of our approach. We perform extensive numerical simulations using
different network instances to validate our theoretical findings, as well as to demonstrate the advantages
of the proposed supply chain management scheme. Keywords: Supply chain management | Quality control | Mixed integer programming | Perishable products |
مقاله انگلیسی |
5 |
Agribusiness time series forecasting using Wavelet neural networks and metaheuristic optimization: An analysis of the soybean sack price and perishable products demand
پیش بینی سری های زمانی کسب و کارهای کشاورزی با استفاده از شبکه های عصبی موج کوچک و بهینه سازی اکتشافی ذهنی متا: یک تحلیل روی قیمت یک گونی سویبان و تقاضای محصولات فاسد شدنی-2018 Brazilian agribusiness is responsible for almost 25% of the country gross domestic product, and companies from this economic sector may have strategies to control their actions in a competitive market. In this way, models to properly predict variations in the price of products and services could be one of the keys to the success in agribusiness. Consistent models are being adopted by companies as part of a decision making process when important choices are based on short or long-term forecasting. This work aims to evaluate Wavelet Neural Networks (WNNs) performance combined with five optimization techniques in order to obtain the best time series forecasting by considering two case studies in the agribusiness sector. The first one adopts the soybean sack price and the second deals with the demand problem of a distinct groups of products from a food company, where nonlinear trends are the main characteristic on both time series. The optimization techniques adopted in this work are: Differential Evolution, Artificial Bee Colony, Glowworm Swarm Optimization, Gravitational Search Algorithm, and Imperialist Competitive Algorithm. Those were evaluated by considering short-term and long-term forecasting, and a prediction horizon of 30 days ahead was considered for the soybean sack price case, while 12 months ahead was selected for the products demand case. The performance of the optimization techniques in training the WNN were compared to the well-established Backpropagation algorithm and Extreme Learning Machine (ELM) assuming accuracy measures. In long-term forecasting, which is considered more difficult than the short-term case due to the error accumulation, the best combinations in terms of precision was reached by distinct methods according to each case, showing the importance of testing different training strategies. This work also showed that the prediction horizon significantly affected the performance of each optimization method in different ways, and the potential of assuming optimization in WNN learning process.
keywords: Agribusiness |Artificial neural networks |Time series forecasting |Metaheuristics |Natural computing |Optimization |
مقاله انگلیسی |
6 |
Joint decisions of shipment consolidation and dynamic pricing of food supply chains
تصمیمات مشترک در مورد تثبیت حمل و نقل و قیمت گذاری پویا در زنجیره تامین مواد غذایی-2017 This paper focuses on a perishable product supply chain with a vendor and multiple retailers. These
retailers, densely spread in a distribution zone, are sensitive to price, delivery time and product quality.
With the aim of optimizing the vendor’s expected long-run average profit during a shipment con
solidation cycle, an analytical model is proposed for this problem. According to the upper bound ex
pressions of the expected long-run average profit, the approximate optimal time policy and freshness
keeping cost are given based on a certain range of time parameter. Our theoretical findings are verified
through a numerical case. Some useful managerial insights are obtained by analyzing the sensitivity of
this model from six perspectives, which are market scenarios, types of perishable products, quality re
quirements of all retailers, cost parameters, line-haul time and vehicle capacity.
Keywords: Shipment consolidation | Perishable products | Freshness-keeping cost | Renew reward theory |
مقاله انگلیسی |
7 |
Inventory competition in a dual-channel supply chain with delivery lead time consideration
رقابت موجودی در زنجیره تامین دو کانال با توجه به زمان تحویل-2017 Aimed at the inventory competition of perishable products in a dual-channel supply chain
with consideration of the delivery lead time in the online direct channel, we extend the
Newsvendor model considering stock-out-based consumer switching behavior to include
the delivery lead time. We examine the retailer’s optimal order quantity decision in the
retail channel and the manufacturer’s optimal inventory level decision in the online direct
channel, explore the manufacturer’s optimal delivery lead time decision in the online di
rect channel, discuss the impact of the product price and consumer switching behavior on
the optimal decisions of supply chain members, and compare the optimal decisions be
tween decentralized and centralized scenarios. The results show that, compared with the
centralized scenario, at least one of the supply chain members will overstock in the decen
tralized scenario and that consumers in the online direct channel enjoy a shorter delivery
lead time and hence better service in the decentralized scenario. Finally, we present nu
merical examples to analyze the impact of relevant parameters on the supply chain mem
bers’ profits and the supply chain efficiency.
Keywords: Supply chain | Dual-channel | Inventory competition | Delivery lead time | Consumer switching behavior |
مقاله انگلیسی |
8 |
Optimizing a vendor managed inventory (VMI) supply chain for perishable products by considering discount: Two calibrated meta-heuristic algorithms
بهینه سازی مدیریت موجودی فروشنده (VMI) زنجیره تامین برای محصولات فاسد شدنی با در نظر گرفتن تخفیف: دو الگوریتم فرا ابتکاری کالیبره-2017 Vendor Managed Inventory (VMI) is one of the inventory management strategies that reduce costs,
increase responsiveness and improve collaboration between the members of supply chain. Although
the VMI can reduce response time and deterioration in perishable supply chain (PSC), but there is a
few reports on using VMI for PSC. In this paper VMI strategy is used for managing the inventory of per
ishable product at two-level supply chain with single vendor and multiple retailers. After passing a speci
fic time of product lifetime that called the critical time, the product would be perished by a probability
distribution function. It is probable that the inventory of product is not sold after the critical time, there
fore the management system will use discount to stimulate demand. Then a proposed model is formu
lated as a nonlinear programming model. The objective function of the proposed model is minimizing
the total cost of supply chain including the cost of fixed ordering, holding, discount, and deterioration
whereas replenishment cycles and order size for retailers and also production time needed to supply
inventory of each retailer can be determined through the proposed model. Since the model is a
NP-hard problem, a Genetic algorithm (GA) and a Particle Swarm Optimization (PSO) algorithm are
developed for solving it appropriately and the results are presented that PSO algorithm has a better
performance for solving of the proposed model in this paper.
Taguchi method is an applied to calibrate the parameters of the algorithms into provide reliable
solution. Finally, the conclusion and further research are presented.
Keywords: Vendor managed inventory | Perishable supply chain | Discount | Genetic algorithm |Particle swarm optimization |
مقاله انگلیسی |
9 |
Virtualization of food supply chains with the internet of things
مجازی سازی زنجیره های تامین مواد غذایی با اینترنت اشیاء-2016 Internet technologies allow supply chains to use virtualizations dynamically in operational management
processes. This will improve support for food companies in dealing with perishable products, unpre
dictable supply variations and stringent food safety and sustainability requirements. Virtualization en
ables supply chain actors to monitor, control, plan and optimize business processes remotely and in real
time through the Internet, based on virtual objects instead of observation on-site. This paper analyses the
concept of virtual food supply chains from an Internet of Things perspective and proposes an architecture
to implement enabling information systems. As a proof of concept, the architecture is applied to a case
study of a fish supply chain. These developments are expected to establish a basis for virtual supply chain
optimization, simulation and decision support based on on-line operational data. In the Internet of
Things food supply chains can become self-adaptive systems in which smart objects operate, decide and
learn autonomously.
Keywords: Virtual objects | Food chains | Internet of things | Traceability | Fish distribution |
مقاله انگلیسی |