Much of the research in facility layout has focused on static layouts where the material handling flow is assumed to be constant during the planning horizon. But in today’s market-based, dynamic environment, layout rearrangement may be required during the planning horizon to maintain layout effectiveness. A few algorithms have been proposed to solve this problem. They include dynamic programmin...

this paper deals with a multi-period fixed charge production-distribution problem associated with backorder and inventories. the objective is to determine the size of the shipments from each supplier and backorder and inventories at each period, so that the total cost incurred during the entire period towards production, transportation, backorder and inventories is minimised. a 0-1 mixed intege...

In this paper, we formally develop techniques that minimize the memory requirements of a target program when synthesizing software from dataflow descriptions of multirate signal processing algorithms. The dataflow programming model that we consider is the synchronous dataflow (SDF) model [21], which has been used heavily in DSP design environments over the past several years. We first focus on ...

We consider the problem of dynamic portfolio optimization in a discrete-time, finite-horizon setting. Our general model considers risk aversion, portfolio constraints (e.g., no short positions), return predictability, and transaction costs. This problem is naturally formulated as a stochastic dynamic program. Unfortunately, with non-zero transaction costs, the dimension of the state space is at...

Nonlinear Knapsack Problems (NKP) are the alternative formulation for the multiple-choice knapsack problems. A powerful approach for solving NKP is dynamic programming which may obtain the global op-timal solution even in the case of discrete solution space for these problems. Despite the power of this solu-tion approach, it computationally performs very slowly when the solution space of the pr...

the markowitz’s optimization problem is considered as a standard quadratic programming problem that has exact mathematical solutions. considering real world limits and conditions, the portfolio optimization problem is a mixed quadratic and integer programming problem for which efficient algorithms do not exist. therefore, the use of meta-heuristic methods such as neural networks and evolutionar...

vehicle routing problem (vrp) is one of the major problems in the transportation and distribution planning. in the most previous studies, the objective of vrp models was distance and vehicle related costs. however in many industrial cases along with routing distance, vehicle loading amount is a factor of cost function. in this paper, we formulate a mixed integer non-linear programming (minlp) m...

Path cost optimization is essential for maneuvering vehicles in a cost effective way. The term cost can be interpreted as fuel consumption, path visibility, probability of being detected, probability of being attacked or a combination of the above. Exact algorithms such as linear programming and dynamic programming can always provide globally optimum solution to such a problem. However, as the ...

bioinformatics, through the sequencing of the full genomes for many species, is increasingly relying on efficient global alignment tools exhibiting both high sensitivity and specificity. many computational algorithms have been applied for solving the sequence alignment problem. dynamic programming, statistical methods, approximation and heuristic algorithms are the most common methods applied t...