Abstract: Individuals are generally associated with different learning styles, which have been explored extensively in recent past. The learning styles refer to the potential of an individual by which s/he can easily comprehend and retain information. Among various learning style models, VARK is the most accepted model which categorizes the learners with respect to their sensory characteristics. Based on the number of preferred learning modes, the learners can be categorized as uni-modal, bi-modal, tri-modal, or quad/multi-modal. Although there is a prevalent belief in the learning styles, however, the model is not being frequently and effectively utilized in the higher education. This research describes the identification model to validate teacher’s didactic practice and student’s performance linkage with the learning styles. The identification model is recommended to check the effective application and evaluation of the various learning styles. The proposed model is a guideline to effectively implement learning styles inventory in order to ensure that it will validate performance linkage with learning styles. If performance is linked with learning styles, this may help eradicate the distrust on learning style theory. For this purpose, a comprehensive study was conducted to compare and understand how VARK inventory model is being used to identify learning preferences and their correlation with learner’s performance. A comparative analysis of the findings of these studies is presented to understand the learning styles of tertiary students in various disciplines. It is concluded with confidence that the learning styles of students cannot be associated with any specific discipline. Furthermore, there is not enough empirical proof to link performance with learning styles.
Abstract: In Japan, meat-type chickens are mainly classified into three categories: (1) Broilers, (2) Branded chickens, and (3) Jidori (Free-range local traditional pedigree chickens). The Jidori chickens are certified by the Japanese Ministry of Agriculture, whilst, for the Branded chickens, there is no regulation with respect to their breed (genotype) or methods for rearing them. It is, therefore, relatively easy for poultry farmers to introduce Branded than Jidori chickens. The Branded chickens are normally fed a low-calorie diet with ingredients such as herbs, which lengthens their breeding period (compared with that of the Broilers) and increases their market value. In the field of inventory management, fast-growing animals such as broilers are categorised as ameliorating items. To the best of our knowledge, there are no previous studies that have explicitly considered smaller sized poultry farmers with limited breeding areas. This study develops an inventory model for a small sized poultry farmer that produces both the Broilers (Product 1) and the Branded chickens (Product 2) with different amelioration rates. The poultry farmer’s total profit per unit of time is formulated as a function of selling prices by using a price-dependent demand function. The existence of a unique optimal selling price for each product, which maximises the total profit, established. It has also been confirmed through numerical examples that, when the breeding area is fixed, the total profit could increase if the poultry farmer reduced the product quantity of Product 1 to introduce Product 2.
Abstract: Today's challenging business environment, with unpredictable demand and volatility, requires a supply chain strategy that handles uncertainty and risks in the right way. Even though inventory models have been previously explored, this paper seeks to apply these concepts on a practical situation. This study involves the inventory replenishment problem, applying techniques that are mainly based on mathematical assumptions and modeling. The primary goal is to improve the retailer’s supply chain processes taking store differences when setting the various target stock levels. Through inventory review policy, picking piece implementation and minimum exposure definition, we were able not only to promote the inventory reduction as well as improve sales results. The inventory management theory from literature review was then tested on a single case study regarding a particular department in one of the largest Latam retail chains.
Abstract: This work proposed a multi-objective mathematical programming approach to select the appropriate supply network elements. The multi-item multi-objective production-distribution inventory model is formulated with possible constraints under fuzzy environment. The unit cost has taken under fuzzy environment. The inventory model and warehouse location model has combined to formulate the production-distribution inventory model. Warehouse location is important in supply chain network. Particularly, if a company maintains more selling stores it cannot maintain individual secondary warehouse near to each selling store. Hence, maintaining the optimum number of secondary warehouses is important. Hence, the combined mathematical model is formulated to reduce the total expenditure of the organization by arranging the network of minimum number of secondary warehouses. Numerical example has been taken to illustrate the proposed model.
Abstract: Just-In-Time (JIT) is a lean manufacturing tool, which provides the benefits of efficiency, and of minimizing unnecessary costs for many organisations. However, the risks arising from these benefits have been disregarded. These risks impact on system processes disrupting the whole supply chain. This paper proposes an inventory model that can simultaneously reduce costs and risks in JIT systems. This model is developed to ascertain an optimal ordering strategy for procuring raw materials by using regular multi-external and local backup suppliers to reduce the total cost of the products, and at the same time to reduce the risks arising from this cost reduction within production systems. Some results that will be illustrated in the second part of this paper are presented.
Abstract: This paper deals with infinite time horizon fuzzy Economic Order Quantity (EOQ) models for deteriorating items with
stock dependent demand rate and nonlinear holding costs by taking deterioration rate θ0 as a triangular fuzzy number (θ0 −δ 1, θ0, θ0 +δ 2), where 1 2 0 0
Abstract: In this paper, a single period inventory model with resalable returns has been analyzed in an imprecise and uncertain mixed environment. Demand has been introduced as a fuzzy random variable. In this model, a single order is placed before the start of the selling season. The customer, for a full refund, may return purchased products within a certain time interval. Returned products are resalable, provided they arrive back before the end of the selling season and are found to be undamaged. Products remaining at the end of the season are salvaged. All demands not met directly are lost. The probabilities that a sold product is returned and that a returned product is resalable, both imprecise in a real situation, have been assumed to be fuzzy in nature.
Abstract: Supply chain management has become more
challenging with the emerging trend of globalization and
sustainability. Lately, research related to perishable products supply
chains, in particular agricultural food products, has emerged. This is
attributed to the additional complexity of managing this type of
supply chains with the recently increased concern of public health,
food quality, food safety, demand and price variability, and the
limited lifetime of these products. Inventory management for agrifood
supply chains is of vital importance due to the product
perishability and customers- strive for quality. This paper
concentrates on developing a simulation model of a real life case
study of a two echelon production-distribution system for agri-food
products. The objective is to improve a set of performance measures
by developing a simulation model that helps in evaluating and
analysing the performance of these supply chains. Simulation results
showed that it can help in improving overall system performance.
Abstract: This paper implements the inventory model developed in the first part of this paper in a simplified problem to simultaneously reduce costs and risks in JIT systems. This model is developed to ascertain an optimal ordering strategy for procuring raw materials by using regular multi-external and local backup suppliers to reduce the total cost of the products, and at the same time to reduce the risks arising from this cost reduction within production systems. A comparison between the cost of using the JIT system and using the proposed inventory model shows the superiority of the use of the inventory model.
Abstract: In this paper, an inventory model with finite and
constant replenishment rate, price dependant demand rate, time
value of money and inflation, finite time horizon, lead time and
exponential deterioration rate and with the objective of maximizing
the present worth of the total system profit is developed. Using a
dynamic programming based solution algorithm, the optimal
sequence of the cycles can be found and also different optimal
selling prices, optimal order quantities and optimal maximum
inventories can be obtained for the cycles with unequal lengths,
which have never been done before for this model. Also, a
numerical example is used to show accuracy of the solution
procedure.
Abstract: Inventory decisional environment of short life-cycle
products is full of uncertainties arising from randomness and
fuzziness of input parameters like customer demand requiring
modeling under hybrid uncertainty. Prior inventory models
incorporating fuzzy demand have unfortunately ignored stochastic
variation of demand. This paper determines an unambiguous optimal
order quantity from a set of n fuzzy observations in a newsvendor
inventory setting in presence of fuzzy random variable demand
capturing both fuzzy perception and randomness of customer
demand. The stress of this paper is in providing solution procedure
that attains optimality in two steps with demand information
availability in linguistic phrases leading to fuzziness along with
stochastic variation. The first step of solution procedure identifies
and prefers one best fuzzy opinion out of all expert opinions and the
second step determines optimal order quantity from the selected
event that maximizes profit. The model and solution procedure is
illustrated with a numerical example.
Abstract: A manufacturing inventory model with shortages with
carrying cost, shortage cost, setup cost and demand quantity as
imprecise numbers, instead of real numbers, namely interval number
is considered here. First, a brief survey of the existing works on
comparing and ranking any two interval numbers on the real line
is presented. A common algorithm for the optimum production
quantity (Economic lot-size) per cycle of a single product (so as
to minimize the total average cost) is developed which works well
on interval number optimization under consideration. Finally, the
designed algorithm is illustrated with numerical example.