International Journal of Supply and Operations Management
Volume:5 Issue: 1, Winter 2018

The grey uncertainty is a new methodology focusing on the study of problems involving small samples and poor information. It deals with uncertain systems with partially known information through generating, excavating, and extracting useful information from what is available. This paper focuses some division solutions for cooperative games, called the equal surplus sharing solutions. A situation, in which a finite set of players can obtain certain grey payoffs by cooperation can be described by a cooperative grey game. In this paper, we consider some grey division rules, namely the equal surplus sharing grey solutions. Further, we focus on a class of equal surplus sharing grey solutions consisting of all convex combinations of these solutions. An application from Operations Research (OR) situations is also given.

In this paper, an economic production quantity (EPQ) inventory model with scrap and rework is developed. The inventory model is for multiple products and all products are manufactured in a single machine. Clearly, the existence of one machine results in limited production capacity and shortages. Therefore, shortages are permitted and partially backordered. We show that the model of the problem is a constrained non-linear program and use GAMS modelling language to solve it. Our objectiveis to minimize the joint total cost of the system and the supply cost of warehouse space, subject to capacity, service level, budget and warehouse space constraints. Subsequently, a nonlinear programming solver BARON is used to solve the model. At the end, numerical examples are provided to demonstrate the applicability of the model in real-world manufacturing problems.To verify the solution obtained and to evaluate the performance of MCDM (Multi Criteria Decision Making) methods , TUKEY test is employed to compare the means of the primary objective values, the mean values of the second objective , and the mean needed CPU time of solving the problem using various methods of MCDM. Also, To compare the methods we used TOPSIS (Technique for Order Preference by Similarity to Ideal Solution). The results show that torabi-hasini method is the most efficient method to solve the model and the solution qualities of the methods differ significantly. Finally, some conclusions and future researches are included.

With the globalization of markets and the advancements in communications, such as the Internet and e-commerce, consumers are directly linked to manufacturers. Consumers can search a product in an offline store and buy it from an online store. This paper investigates the influence channel synchronization on the supplier, the retailer, and the entire supply chain in the dual-channel supply chains. Among synchronization mechanisms, contracts are valuable tools used in both theory and practice to coordinate various supply chains. This study presents a hybrid model with a new demand function and also it surveys the effects of free riding on sales effort in a dual-channel supply chain comprising of one manufacturer and one offline store. Finally, to achieve beneficial outcomes this paper considers a cost-sharing contract to synchronize a dual-channel supply chain. The efficiency of the supply chain can be improved under the stochastic demand solved by the genetic algorithm.

This paper addresses a situation in which a firm is willing to locate several new multi-server facilities in a geographical area to provide a service to his customers within the M/M/m/K queue system. As a new assumption, it is also considered that there is already operating competitors in such system. This paper is going to find the location of facilities in a way that the market share of entering firm is maximized. For this purpose, simultaneous minimization of total cost and maximum idle time in each facility is considered as two objective functions in the model. The total cost consists of two parts: (1) the fixed cost for opening a new facility, and (2) the operational costs regarding to the customers, which depends on travel time to the facility and the waiting time at the facility. In addition, in order to make the problem more adapted to real-world situations, two new constraints on budget and number of the servers in each facility are added to the model. Eventually, to tackle the suggested problem, a non-dominated sorting genetic algorithm (NSGA-II) and a non-dominated ranked genetic algorithm (NRGA) are utilized. Finally, the performance of algorithms are investigated via analyzing a set of test problems.

In this study, an efficient logistics network was designed to optimize both time and cost as the most effective factors using a mathematical model (two-objective fuzzy optimization) in a reverse logistics system. This paper attempted to determine value of goods sent between return products processing centers in any time period, in such a way to minimize total cost and time of delay within supply chain. The fuzzy approach was adopted in order to consider uncertainty in reverse logistics network. The validity of model was measured through a model proposed by Azar Resin Co and then implemented and solved by GAMS software. According to previous studies and implementation of model at smaller scale, the problem revolved around designing NP-hard logistics network. Hence, exact methods cannot solve these problems on large scale, for which Cuckoo algorithm was considered. In order to validate the newly proposed algorithm, results were compared against the exact solution. The results suggested that the proposed Cuckoo algorithm was sufficiently accurate to solve the problem and achieve values similar to exact solution.

This paper considers a popular problem in the investment, the best time and size of investment, using methods of real options in a cooperative game setting. Moreover, it shows a combination of real option theory to invest, combined with a competitive game between two movers in the growth of a general-use asset and cooperative game theory between two movers to catch a network effect. In the model, two firms have similar and interacting investment opportunities. There is a real option for both firms to postpone the investment until they have proper price and production states. There are benefits to a first mover who can create a facility to its own conditions. Also, there is a useful network effect of operating synergy if the first mover successfully motivates the second mover to start production instantaneously by sharing the production facility. So, the first mover has to discover when to create, what capacity to create and what the best economic rent is for using the facility. The second mover has to discover whether to use the first mover’s facility or create its own facility, and if it discovers to create it owns, what better time and size are.

Healthcare Supply Chain Logistics is series of processes, workforce involved across different teams and movement of medicines, surgical equipment, and other products as needed by healthcare professionals to do their job. The aim of Supply Chain in Healthcare is to find the vulnerabilities among departments and propose measures to reduce them. It aims to identify weak areas to achieve targeted health outcome and increases investments in global health. The advantages of efficient Supply Chain in Healthcare is improved processes, efficient utilization of resources, satisfied employees, effective treatment and happy Patients. The significance of the research paper is to analyze possible loopholes in the healthcare and recommended controls which can be applied practically so as to bring improvement in the healthcare. In Hospitals Integrated Supply Chain should be implemented to meet the objectives. The Supply Chain ensures proper linkage of hospitals department, operations, revenue cycle. The Supply Chain can be visualized as a back end program running which is necessary to integrate all the different processes together. The supply chain implemented ensures availability of medicine/product at right time, minimizing inventory wastage, maximizing patient care, coordination in all departments minimizing human error/medication errors. This can be accomplished by using possible measures i.e. integrating subsystems [10], streamlining workflow and use of RFID technologies, standard product code, Global Identification number(GIN).