Assortment planning is the process in which a retailer selects a product line to offer to customers and is a key determinant of a retailer’s profit. We consider the assortment planning problem using a locational choice model for customer product selection and allow for both horizontal and vertical product differentiation. When the distribution of customer preference is unimodal, the optimal sol...

When wireless sensors are randomly deployed in natural environments such as ecological monitoring, military and disaster the initial position of is generally formed through deployment methods air-drop, then, second carried out existing optimization methods, but these will still lead to serious coverage holes. In order solve this problem, paper proposes an algorithm improve rate for sensor netwo...

This paper introduces a new metaheuristic algorithm named the Osprey Optimization Algorithm (OOA), which imitates behavior of osprey in nature. The fundamental inspiration OOA is strategy ospreys when hunting fish from seas. In this strategy, hunts prey after detecting its position, then carries it to suitable position eat it. proposed approach two phases exploration and exploitation mathematic...

This paper proposes a new two-phase hybrid metaheuristic for vehicle routing problem with time windows (VRPTW). The first phase is to minimize the number of routes by means of variable neighborhood search algorithm, while the second phase is mainly aimed at minimizing the total travel distance using tabu search algorithm. Three neighborhood search operators (All-exchange, All-2-opt, All-crossex...

One of the major tasks structural engineers is to reduce building cost. Thus, an effective optimization elements gaining in importance every day. The teaching-learning-based (TLBO), which one metaheuristic algorithms, for optimum design and analysis timber structures under fire accordance with EN 1995 1-2 (Eurocode 5: Design Timber - Part 1- 2 General design), proposed this study. objective fun...

Power loss and voltage uncertainty are the major issues prevalently faced in design of distribution systems. But such can be resolved through effective usage networking reconfiguration that has a combination Distributed Generation (DG) units from networks. In this point view, optimal placement sizing DGs ways to boost performance power The optimum allocation resolves various problems namely, lo...

In this paper we propose an efficient offline job scheduling algorithm working in a grid environment that is based on a relatively new evolutionary metaheuristic called generalized extremal optimization (GEO). We compare our experimental results with those obtained using a very popular evolutionary metaheuristic, the genetic algorithm (GA). The scheduling algorithm implies two-stage scheduling....

Training neural networks is a complex task of great importance in the supervised learning field of research. We intend to show the superiority (time performance and quality of solution) of the new metaheuristic bat algorithm (BA) over other more ―standard‖ algorithms in neural network training. In this work we tackle this problem with five algorithms, and try to over a set of results that could...