Nowadays, environmental issues are considered as the most important factor for competition. In this era, just modern companies can compete with each other and any environment friendly firm plays essential role in gaining more market share. Besides, the 21st century is the era of modern steel and Iranian iron steel industry plays important role in the domestic and international trade only through emphasizing on protection of environment. Therefore, designing a model for strengthening the environmental performance in steel industries is necessary to get some advantages such as energy saving, reducing pollutants, eliminating (declining) of waste, creating value for customers and improving the productivity. In this research, first, we explain green supply chain management and then grey-based DEMATEL Technique is used to identify different factors influencing the green supply chain. Eventually, the green supply chain model (GSCM) is applied for the steel industry. The result determines the most prominence factors of GSCM in Yazd Steel Industry.

Lightweight concrete is a suitable constructional material, which can decrease the weight of buildings and the hazards of earthquake loads. Hence, a large number of research studies have been focused on designing and manufacturing high strength lightweight concretes. In this research using the natural and industrial lightweight aggregates frequently found in the south-east region of Iran (Kerman province), high strength and low cost light weight concretes were manufactured. The effects of aggregate type, aggregate size, and concrete mixture were studied experimentally on the compressive strength of concretes and the density and cost of manufactured samples.

In the present study, the nonlinear forced vibration of symmetric laminated rectangular plates, including Glare fiber metal laminated rectangular plate, is investigated based on the first order shear deformation theory. The boundary condition is considered to be immovable simply support. The Galerkin method is used to obtain the nonlinear ordinary differential equation in terms of an unknown time function. The obtained equation is solved analytically by the multiple time scales method. The obtained results are compared with the numerical solution of the nonlinear ordinary differential equation of motion and a good agreement is found between them.

In this paper, butt joining of Al5083 to commercially pure copper is investigated by friction stir welding method. The effects of transverse welding speed of the tool on the mechanical properties and microstructure of the joint were studied, experimentally. By examining different circumstances, changes in the joint strength were studied and optimized in term of transverse speed. Based on the obtained results, welding speed can improve or reduce the joint strength and an optimum value can be found for the welding speed. Welded Joint that was conducted at the rotation speed of 800 RPM and tool traverse speed of 60 mm min?1 had the highest tensile strength (i.e. about 98% of the weak base metal). Intermetallic compounds were formed in the stir zone and XRD results indicated that Al4Cu9 and Al2Cu were the intermetallic compounds in the stir zone. Micro-cracks formed around the intimatelic particles were observed in the section of joint.

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.

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.

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.

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 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.

This paper introduces the effect of task deterioration in simple assembly line balancing problem. In many realistic assembly lines, a deterioration task is considered when a task is started earlier than the assigned time since the station time is constant and the earliness of the task does not reduce the cycle time. This phenomenon is known as deteriorating tasks. Therefore, we seek an optimal assignment and schedule of tasks in workstations, in order to minimize the number of stations for a given cycle time, which is known as SALBP-1. For this purpose, a mathematical model is proposed. Since the pure SALBP-1 is proved to be NP-hard and considering task deterioration complicates problem further, we propose a genetic algorithm for solving such problem. Several well-known test problems are solved to study the performance of the proposed approach.