A CLASS OF INTEGRATED LOGISTICS NETWORK MODEL UNDER RANDOM FUZZY ENVIRONMENT AND ITS APPLICATION TO CHINESE BEER COMPANY

2009 ◽  
Vol 17 (06) ◽  
pp. 807-831 ◽  
Author(s):  
XIAOYANG ZHOU ◽  
JIUPING XU
Keyword(s):  
Programming Model ◽  
Logistics System ◽  
Fuzzy Constraints ◽  
Logistics Network ◽  
Fuzzy Environment ◽  
Multi Objective Programming ◽  
Production Distribution ◽  
Forward Logistics ◽  
Set Up ◽  
Integrated Logistics

In this paper, we integrated the forward logistics and the reuse reverse logistics to set up a closed-loop integrated logistics system under a random fuzzy environment. A random fuzzy multi-objective programming model was established which can describe the integrated logistics as a cycle of production, distribution, consumption, collection, transportation, recycling, disposal, reuse and redistribution. We then used the expected value operator and the chance-constrained operator to handle the random fuzzy objective functions and the random fuzzy constraints. The solution scheme was pursued by a genetic algorithm based on random fuzzy simulation and compromise approach. And an application to a Chinese beer company was given as an illustration.

A Fuzzy Multi-Objective Stochastic Programming Model for Allocation of Lands in Agricultural Systems

2019 ◽  
pp. 379-413
Keyword(s):  
Agricultural Land ◽  
Programming Model ◽  
Random Variables ◽  
Land Allocation ◽  
Agricultural Lands ◽  
Land Utilization ◽  
Planning Period ◽  
Fuzzy Constraints ◽  
Multi Objective ◽  
Multi Objective Programming

In this chapter, a fuzzy stochastic multi-objective programming model is presented for planning proper allocation of agricultural lands in hybrid uncertain environment so that optimal production of several seasonal crops in a planning year can be achieved. In India, demands of various seasonal crops are gradually increasing due to rapid growth of population, whereas agricultural lands are gradually decreasing due to urbanization. Therefore, it is a huge challenge to the planners to balance this situation by proper planning for the utilization of agricultural lands and resources. From that viewpoint, the methodology is developed in this chapter. To make the model more realistic, the resource parameters incorporated with the problem are considered either in the form of fuzzy numbers (FNs) or random variables having fuzzy parameters. The two main objectives of this agricultural land allocation model are considered as maximizing the production of seasonal agricultural crops and minimizing the total expenditure by utilizing total cultivable lands in a planning period. These objectives are optimized based on the constraints: land utilization, machine-hours, man-days, fertilizer requirements, water supply, etc. As the parameters associated with the constraints are imprecise and uncertain in nature, the constraints are represented using either FN or fuzzy random variables (FRVs). The reasons behind the consideration of fuzzy constraints or fuzzy chance constraints (i.e., the reason for considering the parameters associated with the constraints as FNs or FRVs in the model) are clarified in detail. As a study region, the District Nadia, West Bengal, India is taken into account for allocation of land. To illustrate the potential use of the approach, the model solutions are compared with the existing land allocation of the district.

Optimal Study of the Reverse Logistics Network for Municipal Solid Wastes

2014 ◽  
Vol 519-520 ◽  
pp. 1405-1411
Author(s):  
Zheng Zhang ◽  
Hui Min Ma
Keyword(s):  
Reverse Logistics ◽  
Programming Model ◽  
Solid Wastes ◽  
Chance Constrained Programming ◽  
Municipal Solid Wastes ◽  
Fuzzy Constraints ◽  
Logistics Network ◽  
Reverse Logistics Network ◽  
Constrained Programming ◽  
Fuzzy Parameter

A reverse logistics network for municipal solid wastes is designed. A fuzzy chance constrained programming model that the uncertain recovery quantity described by fuzzy parameter is put forward. The model is solved by transforming it to a deterministic mix integer linear programming model after making the fuzzy constraints clear. A numerical example is provided to demonstrate the feasibility of the model. And this paper analyzes the influence of different confidence level to the model.

Optimal Design for the Manufacturing/Remanufacturing Integrated Logistics Network under Fuzzy Environment

2014 ◽  
Vol 989-994 ◽  
pp. 5547-5550
Author(s):  
Li Gang Sun ◽  
Zheng Zhang
Keyword(s):  
Optimal Design ◽  
Optimization Model ◽  
Fuzzy Optimization ◽  
Capacity Constraints ◽  
Waste Products ◽  
Logistics Network ◽  
Numerical Example ◽  
Fuzzy Environment ◽  
Integrated Logistics

Considering the uncertainty of waste products recovery quantity in consumption areas, a fuzzy optimization model for manufacturing/remanufacturing integrated logistics network with capacity constraints was constructed to determine the number and location of the facilities, the flows between each facility. A numerical example was provided to demonstrate the feasibility of the model.

A Hybrid Fuzzy Multiple Objective Approach to Lotsizing, Pricing, and Marketing Planning Model

2012 ◽  
pp. 271-289 ◽  
Author(s):  
R. Ghasemy Yaghin ◽  
S.M.T. Fatemi Ghomi
Keyword(s):  
Programming Model ◽  
Performance Criterion ◽  
Industrial Case Study ◽  
Multi Objective ◽  
Fuzzy Environment ◽  
Multi Objective Programming ◽  
Inventory Investment ◽  
Marketing Planning ◽  
Proposed Model ◽  
General Demand

Given high variability of demands, a manufacturer has to decide about the products’ prices and lotsizing from a supplier. Due to imprecise and fuzzy nature of parameters such as unit costs and marketing function, a hybrid fuzzy multi-objective programming model including both quantitative and qualitative objectives is proposed to determine the optimal price, marketing expenditure, and lotsize. Considering pricing, marketing, and lotsizing decisions simultaneously, the model maximizes the profit, return on inventory investment (ROII) (as a financial performance criterion), and total customer satisfaction under general demand function with a time-varying pattern in fuzzy environment. After applying appropriate strategies to defuzzify the original model, the equivalent multi-objective crisp model is then transformed by a fuzzy goal programming method. A soft computing, particle swarm optimization (PSO) is applied to solve the final crisp problem. An industrial case study is provided to show the applicability and usefulness of the proposed model and solution method. Finally, concluding remarks are reported.

The Method Research of Production Enterprise Logistics System Integration

2013 ◽  
Vol 734-737 ◽  
pp. 3320-3323
Author(s):  
Kai Wang
Keyword(s):  
System Integration ◽  
Point Of View ◽  
System Capacity ◽  
Enterprise Management ◽  
Logistics System ◽  
Production Scale ◽  
Operation Process ◽  
Enterprise Logistics ◽  
The Individual ◽  
Integrated Logistics

With the expansion of consumer market and production scale, the effect of logistics in the enterprise management is also becoming increasingly prominent. But the individual enterprise's logistics system capacity is limited, can not meet the needs of production and consumption timely and the waste of resources in the operation process are the prominent problems in logistics management. This paper explored the logistics system integration ideas and workable solutions of production enterprise from integrated logistics system point of view.

Cuckoo optimization algorithm in reverse logistics: A network design for COVID-19 waste management

2021 ◽  
pp. 0734242X2110039
Author(s):  
Elham Shadkam
Keyword(s):  
Waste Management ◽  
Network Design ◽  
Optimization Algorithm ◽  
Reverse Logistics ◽  
Heuristic Algorithms ◽  
Programming Model ◽  
Fixed Costs ◽  
Logistics System ◽  
Cuckoo Optimization Algorithm ◽  
Proposed Model

Today, reverse logistics (RL) is one of the main activities of supply chain management that covers all physical activities associated with return products (such as collection, recovery, recycling and destruction). In this regard, the designing and proper implementation of RL, in addition to increasing the level of customer satisfaction, reduces inventory and transportation costs. In this paper, in order to minimize the costs associated with fixed costs, material flow costs, and the costs of building potential centres, a complex integer linear programming model for an integrated direct logistics and RL network design is presented. Due to the outbreak of the ongoing global coronavirus pandemic (COVID-19) at the beginning of 2020 and the consequent increase in medical waste, the need for an inverse logistics system to manage waste is strongly felt. Also, due to the worldwide vaccination in the near future, this waste will increase even more and careful management must be done in this regard. For this purpose, the proposed RL model in the field of COVID-19 waste management and especially vaccine waste has been designed. The network consists of three parts – factory, consumers’ and recycling centres – each of which has different sub-parts. Finally, the proposed model is solved using the cuckoo optimization algorithm, which is one of the newest and most powerful meta-heuristic algorithms, and the computational results are presented along with its sensitivity analysis.

A fuzzy multi-objective programming optimization model for emergency resource dispatching under equitable distribution principle

2021 ◽  
pp. 1-10
Author(s):  
Zhaoping Tang ◽  
Wenda Li ◽  
Shijun Yu ◽  
Jianping Sun
Keyword(s):  
Optimization Model ◽  
Programming Model ◽  
Ideal Point ◽  
Optimal Solution ◽  
Multi Objective ◽  
Emergency Rescue ◽  
Satisfaction Degree ◽  
Multi Objective Programming ◽  
Parameter Interval ◽  
Objective Programming

In the initial stage of emergency rescue for major railway emergencies, there may be insufficient emergency resources. In order to ensure that all the emergency demand points can be effectively and fairly rescued, considering the fuzzy properties of the parameters, such as the resource demand quantity, the dispatching time and the satisfaction degree, the railway emergency resources dispatching optimization model is studied, with multi- demand point, multi-depot, and multi-resource. Based on railway rescue features, it was proposed that the couple number of relief point - emergency point is the key to affect railway rescue cost and efficiency. Under the premise of the maximum satisfaction degree of quantity demanded at all emergency points, a multi-objective programming model is established by maximizing the satisfaction degree of dispatching time and the satisfaction degree of the couple number of relief point - emergency point. Combined with the ideal point method, a restrictive parameter interval method for optimal solution was designed, which can realize the quick seek of Pareto optimal solution. Furthermore, an example is given to verify the feasibility and effectiveness of the method.

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