projects scheduling by the project portfolio selection, something that has its own complexity and its flexibility, can create different composition of the project portfolio. an integer programming model is formulated for the project portfolio selection and scheduling.two heuristic algorithms, genetic algorithm (ga) and simulated annealing (sa), are presented to solve the problem. results of cal...

in today’s dynamic market, organizations must be adaptive to market fluctuations. in addition, studies show that material-handling cost makes up between 20 and 50 percent of the total operating cost. therefore, this paper considers the problem of arranging and rearranging, when there are changes in product mix and demand, manufacturing facilities such that the sum of material handling and rearr...

nowadays, one-dimensional cutting stock problem (1d-csp) is used in many industrial processes and re-cently has been considered as one of the most important research topic. in this paper, a metaheuristic algo-rithm based on the simulated annealing (sa) method is represented to minimize the trim loss and also to fo-cus the trim loss on the minimum number of large objects. in this method, the 1d-...

recently, much attention has been given to stochastic demand due to uncertainty in the real -world. in the literature, decision-making models and suppliers' selection do not often consider inventory management as part of shopping problems. on the other hand, the environmental sustainability of a supply chain depends on the shopping strategy of the supply chain members. the supplier selection pl...

the robust coloring problem (rcp) is a generalization of the well-known graph coloring problem where we seek for a solution that remains valid when extra edges are added. the rcp is used in scheduling of events with possible last-minute changes and study frequency assignments of the electromagnetic spectrum. this problem has been proved as np-hard and in instances larger than 30 vertices, meta-...

The chaotic simulated annealing algorithm for combinatorial optimization problems is examined in the light of the global bifurcation structure of the chaotic neural networks. We show that the result of the chaotic simulated annealing algorithm is primarily dependent upon the global bifurcation structure of the chaotic neural networks and unlike the stochastic simulated annealing infinitely slow...

The Robust Coloring Problem (RCP) is a generalization of the well-known Graph Coloring Problem where we seek for a solution that remains valid when extra edges are added. The RCP is used in scheduling of events with possible last-minute changes and study frequency assignments of the electromagnetic spectrum. This problem has been proved as NP-hard and in instances larger than 30 vertices, meta-...

Genetic algorithm is widely used in optimization problems for its excellent global search capabilities and highly parallel processing capabilities; but, it converges prematurely and has a poor local optimization capability in actual operation. Simulated annealing algorithm can avoid the search process falling into local optimum. A hybrid genetic algorithm based on simulated annealing is designe...