The main purpose of this paper is to generalize the effect of two-phased demand and variable deterioration within the EOQ (Economic Order Quantity) framework. The rate of deterioration is a linear function of time. Th...The main purpose of this paper is to generalize the effect of two-phased demand and variable deterioration within the EOQ (Economic Order Quantity) framework. The rate of deterioration is a linear function of time. The two-phased demand function states the constant function for a certain period and the quadratic function of time for the rest part of the cycle time. No shortages as well as partial backlogging are allowed to occur. The mathematical expressions are derived for determining the optimal cycle time, order quantity and total cost function. An easy-to-use working procedure is provided to calculate the above quantities. A couple of numerical examples are cited to explain the theoretical results and sensitivity analysis of some selected examples is carried out.展开更多
The purpose of this inventory model is to investigate the retailer’s optimal replenishment policy under permissible delay in payments. In this paper, we assume that the supplier would offer the retailer partially per...The purpose of this inventory model is to investigate the retailer’s optimal replenishment policy under permissible delay in payments. In this paper, we assume that the supplier would offer the retailer partially permissible delay in payments when the order quantity is smaller than a predetermined quantity (W). The most inventory systems are usually formed without considering the effect of deterioration of items which deteriorate continuously like fresh fruits, vegetables etc. Here we consider the loss due to deterioration. In real world situation, the demand of some items varies with change of seasons and occasions. So it is more significant if the loss of deterioration is time dependent. Considering all these facts, this inventory model has been developed to make more realistic and flexible marketing policy to the retailer, also establish the result by ANOVA analysis by treating different model parameters as factors.展开更多
It’s known to all that under ideal condition the s to rage cost is kept in lower level when storage management be arranged by Economic Order Quantity(EOQ).Does this mean that any companies should set up their own sto...It’s known to all that under ideal condition the s to rage cost is kept in lower level when storage management be arranged by Economic Order Quantity(EOQ).Does this mean that any companies should set up their own storing system in proportion to the scale of the commodities’ producing or sell ing Furthermore, even if they manage storage in EOQ, because of different oper ation scale, geographical condition or ability borrowing money from financial ma rket, different companies pay unequal cost in storing the same commodity.In thi s paper, except for supplying commodities from our own storage system, the autho rs have analyzed other two supplying ways without whole storage system, they are forward contracts and futures contracts.The authors have discussed variable su pply cost for above different supply measures.According to the cost of each sup ply way, the managers can choose the most economical way in supplying the commod ity and predict the price of futures from storage management arranged by EOQ.Th e summary content is as follow: 1. The comparing of supply cost between forward contracts and storing system a rranged by EOQ. (1) The supply cost from forward contracts (2) The supply cost from storage system arranged by Economic Order Quantity (3) The application example for comparing cost in different supply way 2.The comparing of supply cost between futures going physical and storing syst em arranged by Economic Order Quantity. (1) The supply cost from futures going physical (2) The correlation between futures contracts and storage management arranged b y EOQ (3) The application example for comparing cost in different supply way 3.How does storing system of scale economic affect the price of forward and fu tures contracts (1) How does the price of forward and futures contracts fluctuate (2) How do we calculate the price of a commodity at future point from the cost of scale economic storing (3) How do we operate efficiently in derivatives market by using the cost of sc ale economic storing (4) The application example for analyzing the price of futures 4.The correlation among storage managementforward contracts and futures mark et.展开更多
Purpose-The proposed IT2FMOVMI model intends to concurrently minimize total cost and warehouse space for the single vendor-retailer,multi-item and a consolidated vendor store.Regarding demand and order quantities with...Purpose-The proposed IT2FMOVMI model intends to concurrently minimize total cost and warehouse space for the single vendor-retailer,multi-item and a consolidated vendor store.Regarding demand and order quantities with the deterministic and type-1 fuzzy numbers,we have also formulated the classic/crisp MOVMI model and type-1 fuzzy MOVMI(T1FMOVMI)model.The suggested solution technique can solve both crisp MOVMIand T1FMOVMIproblems.By finding the optimal ordered quantities and backorder levels,the Paretofronts are constructed to form the solution sets for the three models.Design/methodology/approach-A multi-objective vendor managed inventory(MOVMI)is the most recognized marketing and delivery technique for the service provider and the retail in the supply chain in Industry 4.0.Due to the evolving market conditions,the characteristics of the individual product,the delivery period and the manufacturing costs,the demand rate and order quantity of the MOVMI device are highly unpredictable.In such a scenario,a MOVMI system with a deterministic demand rate and order quantity cannot be designed to estimate the highly unforeseen cost of the problem.This paper introduces a novel interval type-2 fuzzy multi-objective vendor managed inventory(IT2FMOVMI)system,which uses interval type-2 fuzzy numbers(IT2FNs)to represent demand rate and order quantities.As the model is an NP-hard,the well-known meta-heuristic algorithm named NSGA-II(Non-dominated sorted genetic algorithm-II)with EKM(Enhanced Karnink-Mendel)algorithm based solution method has been established.Findings-The experimental simulations for the five test problems that demonstrated distinct conditions are considered from the real-datasets of SAPCO company.Experimental study concludes that T1FMOVMI and crisp MOVMI schemes are outclassed by IT2FMOVMI model,offering more accurate Pareto-Fronts and efficiency measurement values.Originality/value-Using fuzzy sets theory,a significant amount of work has been already done in past decades from various points of views to model the MOVMI.However,this is the very first attempt to introduce type-2 fuzzy modelling for the problem to address the realistic implementation of the imprecise parameters.展开更多
文摘The main purpose of this paper is to generalize the effect of two-phased demand and variable deterioration within the EOQ (Economic Order Quantity) framework. The rate of deterioration is a linear function of time. The two-phased demand function states the constant function for a certain period and the quadratic function of time for the rest part of the cycle time. No shortages as well as partial backlogging are allowed to occur. The mathematical expressions are derived for determining the optimal cycle time, order quantity and total cost function. An easy-to-use working procedure is provided to calculate the above quantities. A couple of numerical examples are cited to explain the theoretical results and sensitivity analysis of some selected examples is carried out.
文摘The purpose of this inventory model is to investigate the retailer’s optimal replenishment policy under permissible delay in payments. In this paper, we assume that the supplier would offer the retailer partially permissible delay in payments when the order quantity is smaller than a predetermined quantity (W). The most inventory systems are usually formed without considering the effect of deterioration of items which deteriorate continuously like fresh fruits, vegetables etc. Here we consider the loss due to deterioration. In real world situation, the demand of some items varies with change of seasons and occasions. So it is more significant if the loss of deterioration is time dependent. Considering all these facts, this inventory model has been developed to make more realistic and flexible marketing policy to the retailer, also establish the result by ANOVA analysis by treating different model parameters as factors.
文摘It’s known to all that under ideal condition the s to rage cost is kept in lower level when storage management be arranged by Economic Order Quantity(EOQ).Does this mean that any companies should set up their own storing system in proportion to the scale of the commodities’ producing or sell ing Furthermore, even if they manage storage in EOQ, because of different oper ation scale, geographical condition or ability borrowing money from financial ma rket, different companies pay unequal cost in storing the same commodity.In thi s paper, except for supplying commodities from our own storage system, the autho rs have analyzed other two supplying ways without whole storage system, they are forward contracts and futures contracts.The authors have discussed variable su pply cost for above different supply measures.According to the cost of each sup ply way, the managers can choose the most economical way in supplying the commod ity and predict the price of futures from storage management arranged by EOQ.Th e summary content is as follow: 1. The comparing of supply cost between forward contracts and storing system a rranged by EOQ. (1) The supply cost from forward contracts (2) The supply cost from storage system arranged by Economic Order Quantity (3) The application example for comparing cost in different supply way 2.The comparing of supply cost between futures going physical and storing syst em arranged by Economic Order Quantity. (1) The supply cost from futures going physical (2) The correlation between futures contracts and storage management arranged b y EOQ (3) The application example for comparing cost in different supply way 3.How does storing system of scale economic affect the price of forward and fu tures contracts (1) How does the price of forward and futures contracts fluctuate (2) How do we calculate the price of a commodity at future point from the cost of scale economic storing (3) How do we operate efficiently in derivatives market by using the cost of sc ale economic storing (4) The application example for analyzing the price of futures 4.The correlation among storage managementforward contracts and futures mark et.
基金The authors gratefully acknowledge the helpful comments/feedback received from the reviewers and the editors that have significantly helped enhance the paper.The first author would like to thanks Prof.Pranab K.Muhuri and Dr.Q.M.Danish Lohani for their generous support.
文摘Purpose-The proposed IT2FMOVMI model intends to concurrently minimize total cost and warehouse space for the single vendor-retailer,multi-item and a consolidated vendor store.Regarding demand and order quantities with the deterministic and type-1 fuzzy numbers,we have also formulated the classic/crisp MOVMI model and type-1 fuzzy MOVMI(T1FMOVMI)model.The suggested solution technique can solve both crisp MOVMIand T1FMOVMIproblems.By finding the optimal ordered quantities and backorder levels,the Paretofronts are constructed to form the solution sets for the three models.Design/methodology/approach-A multi-objective vendor managed inventory(MOVMI)is the most recognized marketing and delivery technique for the service provider and the retail in the supply chain in Industry 4.0.Due to the evolving market conditions,the characteristics of the individual product,the delivery period and the manufacturing costs,the demand rate and order quantity of the MOVMI device are highly unpredictable.In such a scenario,a MOVMI system with a deterministic demand rate and order quantity cannot be designed to estimate the highly unforeseen cost of the problem.This paper introduces a novel interval type-2 fuzzy multi-objective vendor managed inventory(IT2FMOVMI)system,which uses interval type-2 fuzzy numbers(IT2FNs)to represent demand rate and order quantities.As the model is an NP-hard,the well-known meta-heuristic algorithm named NSGA-II(Non-dominated sorted genetic algorithm-II)with EKM(Enhanced Karnink-Mendel)algorithm based solution method has been established.Findings-The experimental simulations for the five test problems that demonstrated distinct conditions are considered from the real-datasets of SAPCO company.Experimental study concludes that T1FMOVMI and crisp MOVMI schemes are outclassed by IT2FMOVMI model,offering more accurate Pareto-Fronts and efficiency measurement values.Originality/value-Using fuzzy sets theory,a significant amount of work has been already done in past decades from various points of views to model the MOVMI.However,this is the very first attempt to introduce type-2 fuzzy modelling for the problem to address the realistic implementation of the imprecise parameters.
