PurposeThis paper aims to introduce a novel structure for the physical internet (PI)-enabled sustainable supplier selection and inventory management problem under uncertain ***/methodology/approachTo address hybrid un...
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PurposeThis paper aims to introduce a novel structure for the physical internet (PI)-enabled sustainable supplier selection and inventory management problem under uncertain ***/methodology/approachTo address hybrid uncertainty both in the objective function and constraints, a novel interactive hybrid multi-objective optimization solution approach combining Me-based fuzzy possibilistic programming and interval programming approaches is *** numerical experiments are introduced to validate the feasibility of the established model and the proposed solution ***/valueDue to its interconnectedness, the PI has the opportunity to support firms in addressing sustainability challenges and reducing initial impact. The sustainable supplier selection and inventory management have become critical operational challenges in PI-enabled supply chain problems. This is the first attempt on this issue, which uses the presented novel interactive possibilistic programming method.
Real-world decision-making problems often consist in considering multiple and antithetic objectives. Therefore, multi-objective decision making (MODM) is a practical framework in implicational areas. In this paper, a ...
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Real-world decision-making problems often consist in considering multiple and antithetic objectives. Therefore, multi-objective decision making (MODM) is a practical framework in implicational areas. In this paper, a fuzzy MODM problem is considered, where all of its parameters are defined fuzzily, and a solution inspired by multi-attribute VIKOR method is proposed. The proposed method tries to find fuzzy efficient solution for a problem by minimizing its combinational distance from an ideal and anti-ideal solution. This method can reveal the efficient frontier of the problem. Applicability of the proposed method is shown in an illustrative example and its application is summarized in an investment problem. Both examples show applicability of the proposed method.
Milk-run is a delivery method allowing to move small quantities of a large number of different items with predictable lead times from various suppliers to a customer. The main goal is to minimize the transportation co...
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Milk-run is a delivery method allowing to move small quantities of a large number of different items with predictable lead times from various suppliers to a customer. The main goal is to minimize the transportation cost by minimizing the travel distance and by maximizing vehicle capacities. The effects of uncertainties in arrival times of vehicles and loading times of shipments should also be considered in modeling the milk-run problems. In this paper, a multi-objective linear programming model, an ordinary fuzzymulti-objective linear programming model and an intuitionistic fuzzymulti-objective linear programming model are proposed for the milk-run modeling under time window constraints. The proposed approaches are applied on the real-life data of Borusan Logistics which is one of the largest logistics firms in Turkey and the results are presented.
The intermittent nature of renewable sources, uncertain demand load, and the location of microgrids cause challenges for the proper energy balance between supply and demand. To overcome the issues caused by such chall...
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The intermittent nature of renewable sources, uncertain demand load, and the location of microgrids cause challenges for the proper energy balance between supply and demand. To overcome the issues caused by such challenges and to be economically efficient while minimizing environmental impacts, microgrid design with renewable energy sources has recently attracted the attention of researchers. However, the sustainable microgrid design involving multiple types of demand areas (residential and industrial areas) and seasonal factors has not been explored by researchers. Therefore, this paper investigates the sustainable microgrid design problem with multiple types of demand areas and peer-to-peer energy trading involving seasonal factors and uncertainties to maximize total profit and to minimize environmental costs while satisfying demand. The problem is to determine optimal decisions on the number, location, and capacity of renewable distributed generation sources, energy flows, and seasonal electricity sales prices for the system that includes peer-to-peer trading. A fuzzy multi-objective programming model is developed to handle the uncertainties of demand load and capacity of renewable distributed generation sources. A genetic algorithm is applied to solve the proposed model. Results of computational experiments to assess its effectiveness and efficiency show that the proposed model increases total profit by over 12% and reduces environmental costs by almost 30% compared to the cases of no peer-to-peer energy trading and seasonal factors.
With the urgency of remanufacturing and environmental concerns, closed-loop supply chain (CLSC) networks have drawn the attention of researchers. Although there are many CLSC network models in the literature, most of ...
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With the urgency of remanufacturing and environmental concerns, closed-loop supply chain (CLSC) networks have drawn the attention of researchers. Although there are many CLSC network models in the literature, most of them do not consider uncertainty in general terms. However, practical situations are often not well defined and thus cannot be described precisely in real world CLSCs. In this paper a mixed integer fuzzy mathematical model is proposed for a CLSC network which includes both forward and reverse flows with multiple periods and multiple parts. A fuzzymulti-objective model (FMOM) approach is applied to take into account the fuzziness in the capacity, objectives, demand constraints and also in the reverse rates. Computational results are presented for a number of scenarios to show and validate applicability and flexibility of the model. Results show that the proposed model presents a systematic framework which enables the logistics manager (LM) to adjust the search direction during the solution procedure to obtain a desired satisfactory solution.
This paper presents a new bi-objectivemulti-modal hub location problem with multiple assignment and capacity considerations for the design of an urban public transportation network under uncertainty. Because of the h...
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This paper presents a new bi-objectivemulti-modal hub location problem with multiple assignment and capacity considerations for the design of an urban public transportation network under uncertainty. Because of the high construction costs of hub links in an urban public transportation network, it is not economic to create a complete hub network. Moreover, the demand is assumed to be dependent on the utility proposed by each hub. Thus, the elasticity of the demand is considered in this paper. The presented model also has the ability to compute the number of each type of transportation vehicles between every two hubs. The objectives of this model are to maximize the benefits of transportation by establishing hub facilities and to minimize the total transportation time. Since exact values of some parameters are not known in advance, a fuzzy multi-objective programming based approach is proposed to optimally solve small-sized problems. For medium and large-sized problems, a meta-heuristic algorithm, namely multi-objective particle swarm optimization is applied and its performance is compared with results from the non-dominated sorting genetic algorithm. Our experimental results demonstrated the validity of our developed model and approaches. Moreover, an intensive sensitivity analyze study is carried out on a real-case application related to the monorail project of the holy city of Qom.
In this paper, a new fuzzy bi-objective mathematical model for production-distribution problem under uncertainty for a four-echelon supply chain network design involving of several suppliers, producers, distributors, ...
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In this paper, a new fuzzy bi-objective mathematical model for production-distribution problem under uncertainty for a four-echelon supply chain network design involving of several suppliers, producers, distributors, customers, and a set of transportation modals with different reliability rates are presented. In addition to minimise the total cost of the supply chain, the second objective is maximising reliability rate of the whole proposed system. In order to solve the proposed model, a hybrid two-phase solution procedure is proposed based on possibilistic programming, fuzzy multi-objective programming and an efficient algorithm called self-adaptive differential evolution algorithm. Finally, an extensive comparison by a set of numerical examples with different complexity along with some sensitivity analyses has been reported to explore the efficiency of proposed model as well as the performance of proposed evolutionary algorithm.
In this paper, three simultaneous objectives - material requirements planning (MRP) completion time minimization, total cost minimization, and maximization of the quality of raw materials in an MRP system - are balanc...
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In this paper, three simultaneous objectives - material requirements planning (MRP) completion time minimization, total cost minimization, and maximization of the quality of raw materials in an MRP system - are balanced by using a fuzzy multi-objective programming (F-MOP) model. Crashing the total MRP completion time;that is, reducing the time by increasing the resources, can improve on-time delivery to the customer. The goal is to determine the optimum crashing in an MRP context such that maximum total satisfaction is achieved. The approach proposed in this paper is given in both symmetric and asymmetric cases, and relevant results are presented and discussed. The model can help manufacturers deliver products on time, at low cost, with high quality.
Purpose - This study develops an integrated zero waste discharge planning approach for improving resource efficiency in a pulp-and-paper manufacturing firm. Design/methodology/approach - The objectives of this study a...
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Purpose - This study develops an integrated zero waste discharge planning approach for improving resource efficiency in a pulp-and-paper manufacturing firm. Design/methodology/approach - The objectives of this study are to (1) identify the environmental, technical and social metrics in resource efficiency;(2) utilize fuzzy multi-objective programming and the hybrid particle swarm optimization algorithm to solve the fuzzy problem;and (3) develop an assessment for resource efficiency improvement in an industrial case study. Findings - The findings demonstrate the superiority of hybrid particle swarm optimization algorithm in generating optimal results for a pulp-and-paper manufacturing firm. Practical implications - The findings demonstrate the superiority of hybrid particle swarm optimization algorithm in generating optimal results for a pulp-and-paper manufacturing firm. Originality/value - Resource efficiency is a multi-objective problem in an uncertain environment. In particular, zero waste discharge planning involves minimizing the total cost and maximizing the waste material recovery rate, wastewater reuse, and waste heat recovery.
This paper presents an algorithm using a stepwise programming method to determine the suitable locations for capacitors installations and their ratings in distribution networks. The Voltage and loss reduction capabili...
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ISBN:
(纸本)9783037852668
This paper presents an algorithm using a stepwise programming method to determine the suitable locations for capacitors installations and their ratings in distribution networks. The Voltage and loss reduction capability of nodes are regarded as input indices. The fuzzy inference method is used to obtain capacitor placement suitability of every node. The node having the highest suitability is selected as the compensation node. The energy losses of three time periods and the peak charge are modeled as optimization objective. fuzzy multi-objective programming is used to determine the proper sizes of the capacitors. Considering the each capacitor rating interaction, the circulation calculation method is used to recalculate the capacitor rating for compensated nodes. The results of test system demonstrate the effectiveness and practicability of the method.
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