Algorithms for Investment Project Distribution on Regions

Abstract

This paper proposes an optimization system for solving an NP-hard problem by using several new algorithms and application programs. This study aims to identify a suitable distribution of investment projects across several developed industrial regions. It is assumed that all industrial regions involved have the same economic and strategic characteristics. The problem involves a set of projects that are to be assigned across regions. Each project creates an estimated number of new jobs, and the distribution of projects can be guided by minimizing the maximum total number of newly created jobs. The problem is NP-hard one, and it is difficult to determine the most appropriate distribution. We apply scheduling algorithms in order to solve the analyzed problem. Severalheuristics are developedto obtain the appropriate distribution of newly created jobs across all regions. A branch-and-bound method is employed in order to obtain the exact solution. The performance of the algorithm is demonstrated by the experimental results for a total number of 1850 instances.

Intelligent algorithms and complex system for a smart parking for vaccine delivery center of COVID-19

“…Similarly, the authors in [22] used mixed-integer linear programming to present an inventory-location optimization model for a uniform influenza vaccine distribution between eight groups of populations based on each group's coverage rate. An application of the project distribution was proposed in [2,8,9], where new algorithms were developed to propose several approximate solutions. However, the authors in [2] developed an exact solution.…”

“…An application of the project distribution was proposed in [2,8,9], where new algorithms were developed to propose several approximate solutions. However, the authors in [2] developed an exact solution. In addition, an application of network searching for equity distribution was proposed in [10], where several algorithms based essentially on the subset-sum problem, multi-fit method, and dispatching rule method were proposed.…”

An optimal solution for the budgets assignment problem

“…This probability is chosen as follows. -We chose randomly a number r between [1,Int]. The selected number will be the rth largest unscheduled project index which will be assigned to the municipality having the lower total budget.…”

“…The selected number will be the rth largest unscheduled project index which will be assigned to the municipality having the lower total budget. -In case when the number of unscheduled projects UN p is less than Int, the randomly r will be between [1,UN p ].…”

“…Recently, authors in [1], developed lowers bounds, approximate solutions and an exact method for the problem investment project distribution on regions. The main objective is minimizing the maximum total number of newly created jobs.…”