In this paper, the issue of cooperative (co-op) promotion efforts is addressed in a two-stage supply chain (SC). The investigated SC includes one monopolistic manufacturer and two duopolistic retailers facing different market demands. The customers’ demand is affected by both advertising efforts of the manufacturer and two retailers. Moreover, the retailers compete with each other on local advertising investments within the market. In order to boost the retailers’ advertising level, it is assumed that the manufacturer pays a ratio of the retailers' advertising expenditures. We propose four non-cooperative game scenarios and one cooperative game. Non-cooperative models are established through both Stackelberg and Nash game between two echelons. Moreover, both Cournot and Collusion behaviors are assumed to be followed by two retailers. We develop a promotion cost sharing contract to achieve the channel coordination. Under cooperation model, all SC members seek to reach the highest profit for the entire SC by considering the bargaining power of the SC participants. In each game scenario the optimal solution and unique equilibrium are determined. In addition, a comparison on the advertising level of all SC members along with the value of participation rate are provided. In addition, the feasibility of the cooperative game is discussed and resulted.

This study is an inventory model with consideration of price, stock dependent demand, partially backlogged shortages, and two constant deterioration rates. In this model, demand function depends on price and stock while during the shortage time, demand depends only on price of the product. The deterioration is taken into account as a non-instantaneous, once the item is stocked in retailer’s house, any time deterioration can start with a constant rate for a certain period, then this deterioration rate increases. Shortages are allowed and it is partially backlogged. The corresponding inventory problem constitutes a non-linear constraint optimization problem. Here this problem has been solved using Lingo 15 software and also give 3D graph with the help of MATLAB2010a to show the convexity of the objective function. Finally, to illustrate and validate the inventory model, a numerical example is used considering fixed price. To study the effect of changes of different inventory parameters, a sensitivity analysis has been carried out changing one parameter at a time holding other parameters unchanged.

In this paper, a weighted transfer point location problem is developed in which demand points have probabilistic coordinates. The proposed model is formulated as a probabilistic unconstrained nonlinear programming and the optimum values of decision variables are obtained in the form of probability distribution functions. Because of the complexity in solving the developed model by using the traditional solution approaches, a new stochastic inference method called Probabilistic Role Base (PRB) is developed based on the derived optimum probability distribution functions of the decision variables. This method is used to infer the optimum or near optimum values of all decision variables without solving nonlinear programming model, directly. Finally, to demonstrate the efficiency of the developed algorithm, a numerical example is presented and the results are compared with the optimum solution.

In this paper, an imperfect production inventory system with multi-production run for single vendor and single buyer is studied where the defective items are reworked after several production processes and there is no break down during the rework process. The model is considered for deteriorating items under two delivery policies in order to determine the delivery policy leading to the minimum holding cost of system. The objective of this model is to determine the optimal production setup, number of deliveries and lot size by minimizing the total relevant cost of the proposed vendor-buyer integrated system. To minimize the manufacturer’s and buyer’s holding cost, the supply of finished products are made in small quantities. The total relevant cost of the vendor and the buyer is derived and a numerical example is presented to demonstrate the utility of the model.

This article presents a broad review of Hub location problem (HLP), and its applications. The goal of this article is to provide a review on the newest and most recent publications on Hub location and its application in real world practices since 2013. While, there are some articles which reviewed hub location problem literature but some models were not covered in those articles. In this paper, we try to include capacitated models. We survey advances in analysis and modeling of the hub location problem including its variants and solution algorithm of HLPs. We emphasize the most applicable areas for Marine Transpiration. We show that first, majority of the articles consider network domain, while there are some articles which execute HLP in discrete and continuous domain. Also, the capacitated case attracts more attention in recent years. Finally, the contribution of any type of HLP in the literature is shown schematically.

Municipal solid waste management is one of the main challenges in mega cities. Consequences of landfilling and importance of using alternative energies contribute to the popularity of incineration facilities for city authorities. This article tries to determine the location and allocation decisions on landfills and incineration facilities regarding social and environmental effects. The proposed model minimizes revenue of selling recovered energy and minimizes visual pollution impacts. In addition, the environmental impacts of incineration and landfilling operations are considered as part of constraints. Using the data of Tehran's waste management organization, numerical results show the number of active transfer stations and traffic reduce leading to an increase on waste collection network's efficiency. The results also show a decrease on the landfilling and the amount of hazardous methane emissions as well as an improvement on power and heat energy recovery.

This paper optimizes joint mixed bundling, assortment planning and pricing problems for complementary retail categories that comprise substitutable items. These categories are divided into one primary category and multiple secondary categories and based on cross-selling effect, customers of primary category can opt to buy from other categories. It is assumed that the bundle can comprise one product of each offered complementary categories. A mixed-integer nonlinear programming is proposed that maximizes total profit by optimizing strategy of bundling, assortment selection and prices of single products and the bundle under a maximum-surplus customer choice model. Then because of computational considerations, this model is linearized and converted to a mixed-integer linear programming; whereby exact solution for even large-scale problems can be obtained. The results show that if cross-selling effect between product categories is overlooked or bundling of products is not allowed, then significant profit losses, will be resulted. To the best of our knowledge, this is the first study on bundling strategies in assortment selection decisions.

Deterioration of items is a phenomenon which cannot be neglected as it may provide absurd result. In high-tech business market, deterioration is not always constant but it is time dependent. This paper presents inventory model for time dependent deterioration and time dependent demand under shortages. The mathematical model is provided to optimize the cycle time by minimizing the total cost. Numerical results are discussed to validate the proposed model. The variation of the optimal solution for different parameters is discussed for some instances.

Locating, routing and inventory control in production and distribution centers are the most important decisions in supply chain management. Because of the dependence of these decisions to each other, considering these three aspects simultaneously can have a huge impact on cost reduction. In this study, first, a location-inventory model is developed by utilizing METRIC approach and then, METRIC approach is applied to the location-inventory-routing model. The intended supply chain includes a supplier, distributors and retailers, and the inventory control policy is implemented for both the distributors and retailers. Retailers' demand follows Poisson distribution and the lead-time is also considered probabilistic and is affected by the shortage in distribution centers. Given that the presented model belongs to the class of NP-hard problems, a hybrid metaheuristic solution method is also presented to solve the resulted problem. The proposed hybrid metaheuristic algorithm contains a Simulated Annealing algorithm, to optimize the location-routing problem, and a Genetic Algorithm, to optimize the inventory problem. Also, to evaluate the performance of hybrid algorithm, a comparison between the results of the proposed hybrid algorithm and the exact solutions obtained from Lingo software is provided and, finally, the results are analyzed.

Stochastic scheduling addresses several forms of uncertainty to represent better production environments in the real world. Stochastic scheduling has applications on several areas such as logistics, transportation, production, and healthcare, among others. This paper aims to evaluate the performance of various greedy functions for a GRASP-based approach, under stochastic processing times. Since simulation is used for estimating the objective function, two simulation techniques, Monte Carlo simulation and Common Random Numbers (CRN), are used to compare the performance of different greedy (utility) functions within the GRASP. In order to validate the proposed methodology, the expected total weighted tardiness minimization for a single machine problem was taken as case study. Results showed that both, CRN and Monte Carlo, are not statistically different regarding the expected weighted tardiness results. However, CRN showed a better performance in terms of simulation replications and the confidence interval size for the difference between means. Furthermore, the statistical analysis confirmed that there is a significant difference between greedy functions.