In this paper we consider the solution methods for mixed-integer linear fractional programming (MILFP) models, which arise in cyclic process scheduling problems. We first discuss convexity properties of MILFP problems, and then investigate the capability of solving MILFP problems with MINLP methods. Dinkelbach's algorithm is introduced as an efficient method for solving large scale MILFP proble...

This paper addresses the strategic planning, design and optimization of a network of petrochemical processes under uncertainty and risk considerations. The problem was formulated as a two-stage stochastic mixed-integer nonlinear programming model (MINLP) with parameter uncertainty considered in process yield, raw material and product prices, and upper and lower product market demand. Risk was a...

Trajectory planning for a heavy-duty mining truck near the loading/dumping sites of an open-pit mine is difficult. As opposed to trajectory small-sized passenger car in parking lot, involves complex factors vehicle kinematics and environment. These make concerned scheme mixed-integer nonlinear program (MINLP) incorporated with conditional constraints (denoted as C-MINLP). MINLP solvers can neit...

Employment of unmanned aerial vehicles (UAVs) or drones as swarms coordinating nodes offers multiple advantages for commercial well military applications. However, the complex communication requirements these swarms, coupled with high data rates advanced UAV payloads, require innovative techniques optimizing throughput. Channel capacity being key resource, optimum architecture and network topol...

Mathematical programming has long been recognized as a promising direction to the efficient solution of design, synthesis and operation problems that can gain industry the competitive advantage required to survive in today’s difficult economic environment. Most of the engineering design problems can be modeled as MINLP problems with stochastic parameters. In this paper a novel decomposition alg...

This paper treats the solution of nonlinear optimization problems involving discrete decision variables, also known as generalized disjunctive programming (GDP) or mixed-integer nonlinear programming (MINLP) problems, that arise in process engineering. The key idea is to eliminate the discrete decision variables by adding a set of continuous variables and constraints that represent the discrete...

In a highly competitive scenario, suppliers play a vital role in making a business organization successful. Business of any organization is continuous process and therefore the supplier selection is also dynamic in nature. This is quite natural as the organization’s demand; supplier’s capacity, quality level, lead time, unit part cost and fixed transportation cost of supplier varies with time. ...

This study extends a mathematical model that integrates the location, allocation, inventory replenishment and routing decisions simultaneously. To cope with inherent uncertainty of parameters, we implement a continuous-time Markov process and derive the performance measures of the system. Using the obtained results, the problem is formulated as a mixed integer nonlinear programing model (MINLP)...