scholarly journals Retailer's optimal pricing and replenishment policy for new product and optimal take-back quantity of used product

2018 ◽  
Vol 28 (3) ◽  
pp. 345-353 ◽  
Author(s):  
Nita Shah ◽  
Chetansinh Vaghela
Keyword(s):  
Profit Maximization ◽  
New Product ◽  
Critical Issue ◽  
Point Of View ◽  
Maximization Problem ◽  
Selling Price ◽  
Take Back ◽  
Replenishment Policy ◽  
Total Profit ◽  
Optimal Ordering

In the world of limited resources, recovery of used products for reselling or recycling is a critical issue from the economic and environmental point of view. In this paper, we have assumed that a retailer sells the new product to customers as well as collects and sells the used products. We adopt a price dependent quadratic demand function, and the return of used product as a price and time-dependent linear function. The proposed problem is formulated as a profit maximization problem for the retailer. The objective is to find the optimal selling price, the optimal ordering quantity for the new product, and the optimal quantity of used product simultaneously such that the retailers total profit is maximized. The model is validated by a numerical example and sensitivity analysis is performed for the key parameters.

scholarly journals A Novel Integrated Profit Maximization Model for Retailers under Varied Penetration Levels of Photovoltaic Systems

Energies ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 92
Author(s):  
Ioannis P. Panapakidis ◽  
Nikolaos Koltsaklis ◽  
Georgios C. Christoforidis
Keyword(s):  
Profit Maximization ◽  
Energy Markets ◽  
Maximization Problem ◽  
Selling Price ◽  
Retail Market ◽  
Stochastic Variable ◽  
Wholesale Market ◽  
Market Operation ◽  
Pv Penetration ◽  
Marginal Price

In contemporary energy markets, the Retailer acts as the intermediate between the generation and demand sectors. The scope of the Retailer is to maximize its profits by selecting the appropriate procurement mechanism and selling price to the consumers. The wholesale market operation influences the profits since the mix of generation plants determines the system marginal price (SMP). In the related literature, the SMP is treated as a stochastic variable, and the wholesale market conditions are not taken into account. The present paper presents a novel methodology that aims at connecting the wholesale and retail market operations from a Retailer’s perspective. A wholesale market clearing problem is formulated and solved. The scope is to examine how different photovoltaics (PV) penetration levels in the generation side influences the profits of the Retailer and the selling prices to the consumers. The resulting SMPs are used as inputs in a retailer profit maximization problem. This approach allows the Retailer to minimize economic risks and maximize profits. The results indicate that different PV implementation levels on the generation side highly influences the profits and the selling prices.

Dynamic Pricing and Ordering Policy for Non-Instantaneous Deteriorating Items

2012 ◽  
Vol 433-440 ◽  
pp. 6607-6615
Author(s):  
Reza Maihami ◽  
Isa Nakhai Kamal Abadi
Keyword(s):  
Dynamic Pricing ◽  
Optimal Solution ◽  
Simple Algorithm ◽  
Concave Function ◽  
Deteriorating Items ◽  
Selling Price ◽  
Ordering Policy ◽  
Total Profit ◽  
Optimal Ordering Policy ◽  
Optimal Ordering

In this paper, dynamic pricing and ordering policy for non-instantaneous deteriorating items is developed. Shortage is allowed and partially backlogged where as the backlogging rate is variable and dependent on the waiting time for the next replenishment. The major objective is to determine the optimal selling price and the optimal ordering policy simultaneously such that, the total profit is maximized. We first show that for any given selling price, optimal ordering policy schedule exists and unique. Then, we show that the total profit is a concave function of price. Next, we present a simple algorithm to find the optimal solution. Finally, we solve a numerical example to illustrate the solution procedure and the algorithm.

scholarly journals Simulated Annealing Hyper-Heuristic for a Shelf Space Allocation on Symmetrical Planograms Problem

Symmetry ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1182
Author(s):  
Kateryna Czerniachowska ◽  
Marcin Hernes
Keyword(s):  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
Profit Maximization ◽  
Point Of View ◽  
Maximization Problem ◽  
Shelf Space ◽  
Allocation Model ◽  
Space Allocation ◽  
Effective Decision Making ◽  
Shelf Space Allocation

The allocation of products on shelves is an important issue from the point of view of effective decision making by retailers. In this paper, we investigate a practical shelf space allocation model which takes into account the number of facings, capping, and nesting of a product. We divide the shelf into the segments of variable size in which the products of the specific types could be placed. The interconnections between products are modelled with the help of categorizing the products into specific types as well as grouping some of them into clusters. This results in four groups of constraints—shelf constraints, shelf type constraints, product constraints, position allocation constraints—that are used in the model for aesthetic symmetry of a planogram. We propose a simulated annealing algorithm with improvement and reallocation procedures to solve the planogram profit maximization problem. Experiments are based on artificial data sets that have been generated according to real-world conditions. The efficiency of the designed algorithm has been estimated using the CPLEX solver. The computational tests demonstrate that the proposed algorithm gives valuable results in an acceptable time.

scholarly journals An inventory model for coordinating ordering, pricing and advertisement policy for an advance sales system

2020 ◽  
Vol 30 (3) ◽  
pp. 325-338
Author(s):  
K Aggarwal ◽  
Shuja Ahmed ◽  
Fehmina Malik
Keyword(s):  
Optimal Solution ◽  
Planning Horizon ◽  
Solution Algorithm ◽  
Selling Price ◽  
Advertising Expenditure ◽  
Product Demand ◽  
System A ◽  
Advance Sales ◽  
Total Profit ◽  
Optimal Ordering

In this paper we study a coordinated stock replenishment, pricing, and advertisement problem for an inventory with advance booking system. A single period planning horizon is considered, consisting of both advance sales and spot sales periods. The discount is offered to the customers for booking the product in advance when the replenishment arrives. The product demand is price and advertising expenditure sensitive. This paper aims to find the optimal ordering quantity, selling price, and advertising expenditure of the product, which maximizes the total profit. The solution algorithm is suggested for computing the optimal solution, which is illustrated numerically.

Optimal Inventory Policies for Price and Time Sensitive Demand under Advertisement

2020 ◽  
Vol 13 ◽  
Author(s):  
Nita Shah ◽  
Ekta Patel ◽  
Kavita Rabari
Keyword(s):  
Cycle Time ◽  
Quadratic Function ◽  
Solution Procedure ◽  
Vital Role ◽  
Optimal Number ◽  
Deteriorating Items ◽  
Marginal Effect ◽  
Selling Price ◽  
Total Profit ◽  
Back Order

Aims: This article analyzes an inventory system for deteriorating items. The demand is quadratic function of time and is dependent on time, price and advertisement. Shortages are allowed and partially backlogged. Background: Demand and pricing are the two most crucial factors in inventory policy for any business to be successful. In today’s era of competitive circumstances, any product is promoted through advertisement, which plays a vital role in changing the demand pattern among the community. The marketing and demonstration of an item by time-to-time with fashionable advertisements through well-known media such as TV, radio, newspaper, magazine, etc. However, this idea is not always true for some goods like wheat, vegetables, fruits, food grains, medicines and other perishable goods due to their deteriorating nature and this in turn decreases demand for such goods. Deterioration may define as decay, damage, spoilage, evaporation, obsolescence, pilferage. Hence, deterioration effect is a major part in inventory control theory. So in this article demand rate is considered to be a function of selling price, time and occurrence of advertisement instantaneously. Objective: A solution procedure is obtained to find optimal number of price changes and optimal selling price to maximize the total profit. Method: Classical Optimization. Result: From the sensitivity analysis table, it can be seen that the optimal profit is highly sensible to advertisement coefficient and purchase cost. With an increment in rate of deterioration, selling price decreases. Scale demand has reasonable effect on cycle time and selling price. When the value of increase, the cycle length and profit goes on decreasing. Growth in profit is observed if we increase parameter b, higher will be the profit. Price elasticity is sensible parameter with respect to selling price. If backlogging rate increases, the profit will decreases. The inventory parameters holding cost, back order cost and lost sale cost have marginal effect on total profit. Conclusion: In this article, an inventory model is proposed for deteriorating items with variable demand depends upon the advertisement, selling price of the item and time. Shortages are allowed and partially backlogged and backlogging rate depends on the waiting time for the next replenishment. From this article, we can conclude that the parameters are insensible with respect to optimal profit, cycle time and selling price and rest of the parameters have practical output on total profit.

scholarly journals Genetic Algorithm for the Retailers’ Shelf Space Allocation Profit Maximization Problem

2021 ◽  
Vol 11 (14) ◽  
pp. 6401
Author(s):  
Kateryna Czerniachowska ◽  
Karina Sachpazidu-Wójcicka ◽  
Piotr Sulikowski ◽  
Marcin Hernes ◽  
Artur Rot
Keyword(s):  
Genetic Algorithm ◽  
Profit Maximization ◽  
Allocation Rule ◽  
Maximization Problem ◽  
Shelf Space ◽  
Allocation Model ◽  
Space Allocation ◽  
Shelf Space Allocation ◽  
To Receive

This paper discusses the problem of retailers’ profit maximization regarding displaying products on the planogram shelves, which may have different dimensions in each store but allocate the same product sets. We develop a mathematical model and a genetic algorithm for solving the shelf space allocation problem with the criteria of retailers’ profit maximization. The implemented program executes in a reasonable time. The quality of the genetic algorithm has been evaluated using the CPLEX solver. We determine four groups of constraints for the products that should be allocated on a shelf: shelf constraints, shelf type constraints, product constraints, and virtual segment constraints. The validity of the developed genetic algorithm has been checked on 25 retailing test cases. Computational results prove that the proposed approach allows for obtaining efficient results in short running time, and the developed complex shelf space allocation model, which considers multiple attributes of a shelf, segment, and product, as well as product capping and nesting allocation rule, is of high practical relevance. The proposed approach allows retailers to receive higher store profits with regard to the actual merchandising rules.

scholarly journals Non-submodular model for group profit maximization problem in social networks

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Jianming Zhu ◽  
Smita Ghosh ◽  
Weili Wu ◽  
Chuangen Gao
Keyword(s):  
Social Networks ◽  
Profit Maximization ◽  
Randomized Algorithm ◽  
Political Orientation ◽  
Submodular Functions ◽  
Maximization Problem ◽  
Modular Algorithm ◽  
The Difference ◽  
Group Enterprise ◽  
Theoretical Results

AbstractIn social networks, there exist many kinds of groups in which people may have the same interests, hobbies, or political orientation. Sometimes, group decisions are made by simply majority, which means that most of the users in this group reach an agreement, such as US Presidential Elections. A group is called activated if $$\beta$$ β percent of users are influenced in the group. Enterprise will gain income from all influenced groups. Simultaneously, to propagate influence, enterprise needs pay advertisement diffusion cost. Group profit maximization (GPM) problem aims to pick k seeds to maximize the expected profit that considers the benefit of influenced groups with the diffusion cost. GPM is proved to be NP-hard and the objective function is proved to be neither submodular nor supermodular. An upper bound and a lower bound which are difference of two submodular functions are designed. We propose a submodular–modular algorithm (SMA) to solve the difference of two submodular functions and SMA is shown to converge to a local optimal. We present an randomized algorithm based on weighted group coverage maximization for GPM and apply sandwich framework to get theoretical results. Our experiments verify the efficiency of our methods.

Nonsubmodular Constrained Profit Maximization in Attribute Networks

2021 ◽  
Author(s):  
Liman Du ◽  
Wenguo Yang ◽  
Suixiang Gao
Keyword(s):  
Profit Maximization ◽  
Logistic Function ◽  
Influence Maximization ◽  
Maximization Problem ◽  
Cardinality Constraint ◽  
Three Phase ◽  
Marginal Increment ◽  
The Difference ◽  
Classical Influence ◽  
Influence Maximization Problem

The number of social individuals who interact with their friends through social networks is increasing, leading to an undeniable fact that word-of-mouth marketing has become one of the useful ways to promote sale of products. The Constrained Profit Maximization in Attribute network (CPMA) problem, as an extension of the classical influence maximization problem, is the main focus of this paper. We propose the profit maximization in attribute network problem under a cardinality constraint which is closer to the actual situation. The profit spread metric of CPMA calculates the total benefit and cost generated by all the active nodes. Different from the classical Influence Maximization problem, the influence strength should be recalculated according to the emotional tendency and classification label of nodes in attribute networks. The profit spread metric is no longer monotone and submodular in general. Given that the profit spread metric can be expressed as the difference between two submodular functions and admits a DS decomposition, a three-phase algorithm named as Marginal increment and Community-based Prune and Search(MCPS) Algorithm frame is proposed which is based on Louvain algorithm and logistic function. Due to the method of marginal increment, MPCS algorithm can compute profit spread more directly and accurately. Experiments demonstrate the effectiveness of MCPS algorithm.

scholarly journals Multi-item fuzzy inventory problem with space constraint via geometric programming method

2006 ◽  
Vol 16 (1) ◽  
pp. 55-66 ◽  
Author(s):  
Kumar Mandal ◽  
Kumar Roy ◽  
Manoranjan Maiti
Keyword(s):  
Space Constraint ◽  
Geometric Programming ◽  
Profit Maximization ◽  
Inventory Model ◽  
Programming Method ◽  
Unit Price ◽  
Selling Price ◽  
Inventory Problem ◽  
Set Up ◽  
Fuzzy Inventory

In this paper, a multi-item inventory model with space constraint is developed in both crisp and fuzzy environment. A profit maximization inventory model is proposed here to determine the optimal values of demands and order levels of a product. Selling price and unit price are assumed to be demand-dependent and holding and set-up costs sock dependent. Total profit and warehouse space are considered to be vague and imprecise. The impreciseness in the above objective and constraint goals has been expressed by fuzzy linear membership functions. The problem is then solved using modified geometric programming method. Sensitivity analysis is also presented here.

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