International Journal of Applied Metaheuristic Computing, 2017
Optimization is an important fields of study in science where researchers seek to make the best a... more Optimization is an important fields of study in science where researchers seek to make the best and most practical decisions. Solving real optimization problems is an intractable issue which calls for generating an approximate using meta-heuristic algorithms. This study proposes a meta-heuristic algorithm which mainly searches the infeasible region. In this approach, the authors start from an infeasible solution, and while they try to get near to the feasible region, they ensure that the best value is kept for the objective function. The algorithm examines the space in such terms as Infeasibility and Objective Functions, Neighborhood Limited Area, Random Smart Points, and the calculation of new solutions. The algorithm can convert an infeasible solution to an appropriate corresponding feasible solution by applying a simple mathematical methodology. Finally, to test the efficiency of our algorithm, a sample random MIP problem and a hard benchmark TSP instance are solved and discussed...
Abstract: An α-labeling of a graph G is a graceful labeling of graph G with an additional propert... more Abstract: An α-labeling of a graph G is a graceful labeling of graph G with an additional property. In this paper the existence and construction of an α-labeling of the graph C4a ∪ C4b ∪ C4c is discussed. Key-Words: Graph Labeling, α-labeling, Graceful Valuation 1.
Among scientific fields of study, mathematical programming has high status and its importance has... more Among scientific fields of study, mathematical programming has high status and its importance has led researchers to develop accurate models and effective solving approaches to addressing optimization problems. In particular, metaheuristic algorithms are approximate methods for solving optimization problems whereby good (not necessarily optimum) solutions can be generated via their implementation. In this study, we propose a population-based metaheuristic algorithm according to chemotherapy method to cure cancers that mainly search the infeasible region. As in chemotherapy, Chemotherapy Science Algorithm (CSA) tries to kill inappropriate solutions (cancers and bad cells of the human body); however, this would inevitably risk incidentally destroying some acceptable solutions (healthy cells). In addition, as the cycle of cancer treatment repeats over and over, the algorithm is iterated. To align chemotherapy process with the proposed algorithm, different basic terms and definitions in...
... 3, No. 3, pp 189-212 Fall 2009 Integrated Procurement, Production and Delivery Scheduling in ... more ... 3, No. 3, pp 189-212 Fall 2009 Integrated Procurement, Production and Delivery Scheduling in a Generalized three Stage Supply Chain Naser Nikandish1∗ , Kourosh Eshghi2, S. Ali Torabi3 ... Page 2. 190 Nikandish, Eshghi and Torabi Figure 1 A typical three-stage supply chain. ...
International Journal of Applied Metaheuristic Computing, 2017
Optimization is an important fields of study in science where researchers seek to make the best a... more Optimization is an important fields of study in science where researchers seek to make the best and most practical decisions. Solving real optimization problems is an intractable issue which calls for generating an approximate using meta-heuristic algorithms. This study proposes a meta-heuristic algorithm which mainly searches the infeasible region. In this approach, the authors start from an infeasible solution, and while they try to get near to the feasible region, they ensure that the best value is kept for the objective function. The algorithm examines the space in such terms as Infeasibility and Objective Functions, Neighborhood Limited Area, Random Smart Points, and the calculation of new solutions. The algorithm can convert an infeasible solution to an appropriate corresponding feasible solution by applying a simple mathematical methodology. Finally, to test the efficiency of our algorithm, a sample random MIP problem and a hard benchmark TSP instance are solved and discussed...
Abstract: An α-labeling of a graph G is a graceful labeling of graph G with an additional propert... more Abstract: An α-labeling of a graph G is a graceful labeling of graph G with an additional property. In this paper the existence and construction of an α-labeling of the graph C4a ∪ C4b ∪ C4c is discussed. Key-Words: Graph Labeling, α-labeling, Graceful Valuation 1.
Among scientific fields of study, mathematical programming has high status and its importance has... more Among scientific fields of study, mathematical programming has high status and its importance has led researchers to develop accurate models and effective solving approaches to addressing optimization problems. In particular, metaheuristic algorithms are approximate methods for solving optimization problems whereby good (not necessarily optimum) solutions can be generated via their implementation. In this study, we propose a population-based metaheuristic algorithm according to chemotherapy method to cure cancers that mainly search the infeasible region. As in chemotherapy, Chemotherapy Science Algorithm (CSA) tries to kill inappropriate solutions (cancers and bad cells of the human body); however, this would inevitably risk incidentally destroying some acceptable solutions (healthy cells). In addition, as the cycle of cancer treatment repeats over and over, the algorithm is iterated. To align chemotherapy process with the proposed algorithm, different basic terms and definitions in...
... 3, No. 3, pp 189-212 Fall 2009 Integrated Procurement, Production and Delivery Scheduling in ... more ... 3, No. 3, pp 189-212 Fall 2009 Integrated Procurement, Production and Delivery Scheduling in a Generalized three Stage Supply Chain Naser Nikandish1∗ , Kourosh Eshghi2, S. Ali Torabi3 ... Page 2. 190 Nikandish, Eshghi and Torabi Figure 1 A typical three-stage supply chain. ...
Uploads