Sharif Digital Repository

In this paper, all graphs are finite without loops or multiple edges, and all parameters are positive integers. The symbols |A|, Pn, and Cn denote the cardinality of set A, a snake, and a cycle with n edges, respectively. A sequence of numbers in parentheses or square brackets indicates the labels of vertices of a graph or subgraph under consideration according to whether it is a snake or cycle, respectively  

In this paper, a fuzzy random minimum cost flow problem is presented. In this problem, cost parameters and decision variables are fuzzy random variables and fuzzy numbers respectively. The object of the problem is to find optimal flows of a capacitated network. Then, two algorithms are developed to solve the problem based on Er-expected value of fuzzy random variables and chance-constrained programming. Furthermore, the results of two algorithms will be compared. An illustrative example is also provided to clarify the concept  

In the literature, substantial researches have been carried out on supply chain coordination. The majority of these studies suggest a mechanism that enforces the supply chain members to follow the strategies that produce the equilibrium of an integrated supply chain. Moreover, most of researches do not consider the competition among supply chains  

The general goal of the facility layout problem is to arrange a given number of facilities to minimize the total cost associated with the known or projected interactions between them. One of the special classes of the facility layout problem is the Single Row Facility Layout Problem (SRFLP), which consists of finding an optimal linear placement of rectangular facilities with varying dimensions on a straight line. This paper first presents and proves a theorem to find the optimal solution of a special case of SRFLP. The results obtained by this theorem prove to be very useful in reducing the computational efforts when a new algorithm based on tabu search for the SRFLP is proposed in this... 

In this paper, we have discussed the results of sensitivity analysis in a payoff matrix of the Matching Pennies game. After representing the game as a LP model, the sensitivity analysis of the elements of the payoff matrix is presented. The game value and the optimal strategies for different values of parameters are determined and compared  

Ant colony optimization (ACO) is a well-known metaheuristic in which a colony of artificial ants cooperate in exploring good solutions to a combinatorial optimization problem. In this paper, an ACO algorithm is presented for the graph coloring problem. This ACO algorithm conforms to max-min ant system structure and exploits a local search heuristic to improve its performance. Experimental results on DIMACS test instances show improvements over existing ACO algorithms of the graph coloring problem  

The graph colouring problem, as an important NP-complete problem, is considered in this paper and a hybrid meta-heuristic approach is developed to solve it. The initial solution of the algorithm, generated by a heuristic method, is used by a simulated annealing (SA) approach to generate new solutions until no progress in a number of solutions reported. At this stage, the algorithm will use a tabu search routine and this local search operator will be followed for some iterations. After finding a better solution, the algorithm is again followed through SA. Efficiency of the algorithm is showed through various experiments on well-known benchmark problems of DIMACS. Comparison with the available... 

The one-dimensional cutting stock problem has many applications in industries and during the past few years has been one of the centers of attention among the researchers in the field of applied operations research. In this paper, a revised version of Ant Colony Optimization (ACO) technique is presented to solve this problem. This paper is a sequel to the previous ACO algorithm presented by the authors. In this algorithm, according to some probabilistic rules, artificial ants will select cutting patterns and generate a feasible solution. Computational results show the high efficiency and accuracy of the proposed algorithm for solving one- dimensional cutting stock problem  

Graceful labeling is one of the best known labeling methods of graphs. Despite the large number of papers published on the subject of graph labeling, there are few particular techniques to be used by researchers to gracefully label graphs. In this paper, first a new approach based on the mathematical programming technique is presented to model the graceful labeling problem. Then a “branching method” is developed to solve the problem for special classes of graphs. Computational results show the efficiency of the proposed algorithm for different classes of graphs. One of the interesting results of our model is in the class of trees. The largest tree known to be graceful has at most 27 vertices... 

In this paper, we will discuss two special classes of mathematical programming models with fuzzy random variables. In the first model, a linear programming problem with fuzzy decision variables and fuzzy random coefficients is introduced. Then an algorithm is developed to solve the model based on fuzzy optimization method and fuzzy ranking method. In the second model, a fuzzy random quadratic spanning tree problem is presented. Then the proposed problem is formulated and solved by using the scalar expected value of fuzzy random variables. Furthermore, illustrative numerical examples are also given to clarify the methods discussed in this paper  

Graceful labeling is one of the best known labeling methods of graphs. Despite the large number of papers published on the subject of graph labeling, there are few particular techniques to be used by researchers to gracefully label graphs. In this paper, first a new approach based on the mathematical programming technique is presented to model the graceful labeling problem. Then a “branching method” is developed to solve the problem for special classes of graphs. Computational results show the efficiency of the proposed algorithm for different classes of graphs. One of the interesting results of our model is in the class of trees. The largest tree known to be graceful has at most 27 vertices... 

In this paper, a "Game Theory" approach for finding an optimal path in a "Wireless Sensor Network" is discussed. WSN is one of the most interesting research fields in the communication networks, and is the center of attention in recent years. In our model, a pricing and payment technique is presented to obtain an optimal path in a WSN by considering reliability, energy and traffic load. The proposed algorithm is able to find a path which improves network lifetime, load distribution and path reliability  

The one-dimensional cutting stock problem, has so many applications in lots of industrial processes and during the past few years has attracted so many researchers’ attention all over the world. In this paper a metaheuristic method based on ACO is presented to solve this problem. In this algorithm, based on designed probabilistic laws, artificial ants do select various cuts and then select the best patterns. Also because of the problem framework, effective improvements has been made to problem solving process. The results of that algorithm in sample problems, show high efficiency of the algorithm in different levels of problems  

In this paper, a new algorithm for solving the shortest loop design problem is presented. The shortest loop design problem is to find the shortest loop for an automated guided vehicle covering at least one edge of each department of a block layout. In this paper, first it is shown that this problem can be represented as a graph model. The properties of the presented model enable us to design a meta-heuristic based on ant colony system algorithm for solving the shortest loop design problem. Computational results show the efficiency of our algorithm in compare to the other techniques  

In this paper, a fuzzy approach is applied to special classes of integer programming problems with all diierent constraints. In the rst model, a fuzzy integer programming model is developed to represent the all-diierent constraints in mathematical programming. In order to solve the proposed model, a new branching scheme for the Branch and Bound algorithm is also presented. In the second model, a special class of large-scale multi-objective fuzzy integer programming problems with all-diierent constraints is introduced. A solution method for the proposed model is also developed by using the decomposition technique, weighting method and Branch and Bound algorithm. An illustrative numerical... 

In this paper, a fuzzy random minimum cost flow problem is presented. In this problem, cost parameters and decision variables are fuzzy random variables and fuzzy numbers respectively. The object of the problem is to find optimal flows of a capacitated network. Then, two algorithms are developed to solve the problem based on Er-expected value of fuzzy random variables and chance-constrained programming. Furthermore, the results of two algorithms will be compared. An illustrative example is also provided to clarify the concept  

In this paper, seller-buyer supply chain coordination with general side-payment contracts is introduced to gain the maximum possible chain profit. In our model, the logistics costs for both buyer and seller are considered and the final demand is also supposed to be a decreasing function of the retail price. Since parties aim to maximize their individual profits, the contractual parameters are set in a way that these decisions become aligned with system optimal decisions. Therefore, a side payment contract is suggested in our model to assign the chain surplus profit to the chain members such that they have no intention to leave the coalition. Then, we change the contract into a quantity... 

The purpose of this paper is to study and review some major impacts of the disasters during the past 105 years and develop a new theoretical classification of disasters. Design/methodology/approach– A detailed study of disasters in the world during the period (1900‐2005) has been obtained from the recent published sources. In that period more than 40 lessons have been reported based on statistical data analysis of disasters. Furthermore, a two‐dimensional probability density function is developed to categorize the different types of disasters. This paper studies and reviews some major impacts of disasters during the past 105 years and summarizes some major lessons for the future.... 

In this paper, we consider a dual-sourcing model with constant demand and stochastic lead times. Two suppliers may be different in terms of purchasing prices and lead-time parameters. The ordering takes place when the inventory level depletes to a reorder level, and the order is split among two suppliers. Unlike previous works in the order splitting literature, the supply lead time between vendor and buyer as well as unit purchasing prices is considered to be order quantity dependent. The proposed model finds out the optimal reorder point, order quantity and splitting proportion, using a solution procedure. Numerical results show that neglecting the relationship between ordering batch size... 

Usually, resources are short in supply when earthquakes occur. In such emergency situations, disaster relief organizations must use these scarce resources efficiently to achieve the best possible emergency relief. This paper therefore proposes a multi-objective, multi-mode, multi-commodity, and multi-period stochastic model to manage the logistics of both commodities and injured people in the earthquake response. Also, a robust approach is developed and used to make sure that the distribution plan performs well under the various situations that can follow an earthquake. Afterwards, it proposes a solution methodology according to hierarchical objective functions and uses it to illustrate the...