Local search is a heuristic technique for solving hard optimization problems and is widely used in practice. Suppose that a certain optimization problem can be formulated as finding a solution maximizing an objective function in the solution space. A local search algorithm for this problem would start from an arbitrary or carefully chosen solution, then iteratively move to other solutions by ma...

We study a complex optimization problem that arises due to an emerging trend in distribution logistics. The problem involves the integration of an inventory management problem and the vehicle routing problem with time windows, both of which are known to be NP-hard. We describe a collaborative approach to solve this problem in real-time. The novelty of our approach lies in the tight algorithmic ...

Ant System, the first Ant Colony Optimization algorithm, showed to be a viable method for attacking hard combinatorial optimization problems. Yet, its performance, when compared to more fine-tuned algorithms, was rather poor for large instances of traditional benchmark problems like the Traveling Salesman Problem. To show that Ant Colony Optimization algorithms could be good alternatives to exi...

We present a theoretical study of a problem arising in database query optimization [1], which we call as The Common Prefix Problem. We present a (1 − o(1)) factor approximation algorithm for this problem, when the underlying graph is a binary tree. We then use a result of Feige and Kogan [2] to show that even on stars, the problem is hard to approximate.

Assortment optimization is an important problem that arises in many practical applications such as retailing and online advertising. In such settings, the goal is to select a subset of items to offer from a universe of substitutable items in order to maximize expected revenue when consumers exhibit a random substitution behavior. We consider a capacity constrained assortment optimization proble...

in this paper, we introduce a model  to optimization of milk run system that is one of vrp problem with time window and uncertainty in inventory. this approach led to the routes with minimum cost of transportation while satisfying all inventory in a given bounded set of uncertainty .the problem is formulated as a robust optimization problem. since the resulted problem illustrates that grows up ...

We describe a general-purpose method for finding high-quality solutions to hard optimization problems, inspired by self-organized critical models of co-evolution such as the Bak-Sneppen model. The method, called Extremal Optimization, successively eliminates extremely undesirable components of sub-optimal solutions, rather than “breeding” better components. In contrast to Genetic Algorithms whi...

The maximum clique problem (MCP) is to determine a sub graph of maximum cardinality. A clique is a The corresponding optimization problem i.e. finding the maximum Maximum Clique Problem. in Handbook of Combinatorial. Common theme of every optimization problem: of semidefinite programming, A module on combinatorial optimization, Selected topics: The largest clique (i.e., complete subgraph)! In “...