This paper presents production-inventory models for deteriorating items with increasing-steady-decreasing demand pattern under the effect of inflation and time value of money. This type of demand behavior can be observed in some fashion products or seasonal products in general. Shortages are allowed with partial backlogging of demand and a two-parameter Weibull-distribution function is used for the deterioration of items in order to make the models more generalized and realistic. The models generate optimal values of initial production run time, onset of shortages, production recommencement time, and total production quantity that minimizes the total relevant costs of production and inventory for any given set of system parameters. Various possible production strategies available for items with variable demand pattern are examined to determine the optimal production strategy. The discounted cash flow approach and trust region optimization methods are used to obtain the optimal results. The Numerical examples and sensitivity analysis show that the optimal production strategy may vary with changes in system parameters.
In recent years, development of freight transport industry has led to fierce competition among transportation companies and therefore carrier-pricing issue has received more attention by researchers. This paper studies pricing and fleet management decisions for full-truckload freight carriers, which compete on a road network. We propose a game theory approach under two scenarios. In the first, we model the non-cooperative game wherein the carriers announce their prices simultaneously in competition; in the second, we allow the carriers to share their information and announce their prices while participating in cooperation. We show that carriers can reach the highest profit level in the latter scenario; subsequently, a bargaining game is discussed as a scheme to share the extra joint profit.
In this paper, wire electrical discharge machining of WC-Co composite is studied. Influence of taper angle, peak current, pulse-on time, pulse-off time, wire tension and dielectric flow rate are investigated for material removal rate (MRR) and surface roughness (SR) during intricate machining of a carbide block. In order to optimize MRR and SR simultaneously, grey relational analysis (GRA) is employed along with Taguchi method. Through GRA, grey relational grade is used as a performance index to determine the optimal setting of process parameters for multiple machining characteristics. Analysis of variance (ANOVA) shows that the taper angle and pulse-on time are the most significant parameters affecting the multiple machining characteristics. Confirmatory results, proves the potential of GRA to optimize process parameters successfully for multi-machining characteristics.
This study investigates minimizing the number of weighted tardy jobs on a single machine when jobs are delivered to either customers or next station in various size batches. In real world, this issue may happen within a supply chain in which delivering goods to customers entails costs. Under such circumstances, keeping completed jobs to deliver in batches may result in reducing delivery costs; nevertheless, it may add to the tardy jobs, which in turn leads to higher costs. In literature review, minimizing the number of weighted tardy jobs is known as NP-Hard problem, so the present issue aiming at minimizing the costs of delivering, in addition to the aforementioned objective function, remains an NP-Hard problem. In this study, the issue is assessed where the customers are numerous, and a mathematical model is presented. We also present a meta-heuristic method based on simulated annealing (SA) and the performance of the SA is examined versus exact solutions.
This study was carried out on 621 schoolboys with age range of 12-17 years in Junior and Senior Secondary Schools in Odeda area of Odeda local government in Ogun State, Nigeria. Different anthropometric data were collected from these boys. It was observed from the results that all anthropometric dimensions of the school children increase with their age. Moreover, there exists a little difference between mean values of different anthropometric dimensions between the boys of 12-13 years (2.9% to 8.8%), 14-15 years (1.3% to 9.9%), and 16-17 years (1.4% to 5.5%). But the said differences become much higher (16.2% to 42.4%) when the same were compared between the children of 12 years and 17 years. Therefore, it can be said that the design of furniture for the children of 12 years will not match the children of 17 years. If single furniture is designed by considering dimensions of the children from 12 years to 17years, it will also not suit the children of all age groups. Therefore, in the present investigation, all the students have been divided into three combined age groups, e.g., 12-13 years, 14-15 years, and 16-17 years, and the percentile values (5th, 50th and 95th) of anthropometric measures, which will be helpful for designing of the classroom furniture.
One of the primary concerns on many traditional capacitated facility location/network problems is to consider transportation and setup facilities in one single objective function. This simple assumption may lead to misleading solutions since the cost of transportation is normally considered for a short period time and, obviously, the higher cost of setting up the facilities may reduce the importance of the transportation cost/network. In this paper, we introduce capacitated facility location/network design problem (CFLNDP) with two separate objective functions in forms of multi-objective with limited capacity. The proposed model is solved using a new hybrid algorithm where there are two stages. In the first stage, locations of facilities and design of fundamental network are determined and in the second stage demands are allocated to the facilities. The resulted multi-objective problem is solved using Lexicography method for a well-known example from the literature with 21 node instances. We study the behaviour of the resulted problem under different scenarios in order to gain insight into the behaviour of the model in response to changes in key problem parameters.
The terminal condition of inventory level to be zero at the end of the cycle time adopted by Soni and Shah (2008, 2009) is not viable when demand is stock-dependent. To rectify this assumption, we extend their model for (1) an ending – inventory to be non-zero; (2) limited floor space; (3) a profit maximization model; (4) selling price to be a decision variable, and (5) units in inventory deteriorate at a constant rate. The algorithm is developed to search for the optimal decision policy. The working of the proposed model is supported with a numerical example. Sensitivity analysis is carried out to investigate critical parameters.
In this paper, a new formulation model for cellular manufacturing system (CMS) design problem is proposed. The proposed model of this paper considers assembly operations and product structure so that it includes the scheduling problem with the formation of manufacturing cells, simultaneously. Since the proposed model is nonlinear, a linearization method is applied to gain optimal solution when the model is solved using direct implementation of mixed integer programming. A new genetic algorithm (GA) is also proposed to solve the resulted model for large-scale problems. We examine the performance of the proposed method using the direct implementation and the proposed GA method. The results indicate that the proposed GA approach could provide efficient assembly and product structure for real-world size problems.
This paper deals with an inventory model, which considers the impact of marketing strategies such as pricing and advertising as well as the displayed inventory level on the demand rate of the system. In addition, the demand rate during the stock-out period differs from that during the stock-in period by a function varied on the waiting time up to the beginning of the next cycle. Shortage are allowed and partially backlogged. Here, the deterioration rate is assumed to follow the Weibull distribution. Considering all these factors with others, different scenarios of the system are investigated. To obtain the solutions of these cases and to illustrate the model, an example is considered. Finally, to study the effects of changes of different parameters of the system, sensitivity analyses have been carried out with respect to the different parameters of the system.
This research defines a new application of mathematical modeling to design a cellular manufacturing system integrated with group scheduling and layout aspects in an uncertain decision space under a supply chain characteristics. The aim is to present a mixed integer programming (MIP) which optimizes cell formation, scheduling and layout decisions, concurrently where the suppliers are required to operate exceptional products. For this purpose, the time in which parts need to be operated on machines and also products & apos; demand are uncertain and explained by set of scenarios. This model tries to optimize expected holding cost and the costs regarded to the suppliers network in a supply chain in order to outsource exceptional operations. Scheduling decisions in a cellular manufacturing framework is treated as group scheduling problem, which assumes that all parts in a part group are operated in the same cell and no inter-cellular transfer is required. An efficient hybrid method made of genetic algorithm (GA) and simulated annealing (SA) will be proposed to solve such a complex problem under an optimization rule as a sub-ordinate section. This integrative combination algorithm is compared with global solutions and also, a benchmark heuristic algorithm introduced in the literature. Finally, performance of the algorithm will be verified through some test problems.