Primal heuristics are an important component of state-of-the-art codes for mixed integer nonlinear programming (MINLP). In this article we give a compact overview of primal heuristics for MINLP that have been suggested in the literature of recent years. We sketch the fundamental concepts of different classes of heuristics and discuss specific implementations. A brief computational experiment sh...

Dynamic lot sizing problem is one of the significant problem in industrial units and it has been considered by many researchers. Considering the quantity discount in purchasing cost is one of the important and practical assumptions in the field of inventory control models and it has been less focused in terms of stochastic version of dynamic lot sizing problem. In this paper, stochastic dynamic...

The optimal scheduling of crude-oil operation in refineries has been studied by various groups during the past decade, leading to different mixed integer linear programming or mixed nonlinear programming formulations. This paper proposes a new MINLP formulation with an oil residency time constraint and common pipeline transportation that is based on single-operation sequencing (SOS). An effecti...

The optimal scheduling of crude-oil operation in refineries has been researched by various groups during the past decade. Different mixed integer linear programming or mixed nonlinear programming formulations are derived. This paper proposes a novel MINLP formulation with multiple charging tanks charging a distiller overlapingly and oil residency time constraint that is based on multi-operation...

although several papers have studied no-idle scheduling problems, they all focus on flow shops, assuming one processor at each working stage. but, companies commonly extend to hybrid flow shops by duplicating machines in parallel in stages. this paper considers the problem of scheduling no-idle hybrid flow shops. a mixed integer linear programming model is first developed to mathematically form...

A hybrid particle swarm optimization algorithm which includes two alternative gradient-based methods for handling constraints has been proposed to solve process synthesis and design problems which involve continuous and binary variables and equality and inequality constraints (a mixed integer non-linear programming problem, MINLP). The first method for handling constraints uses the Newton-Raphs...

This paper investigates an order allocation problem of a manufacturer/buyer among multiple suppliers under the risks of supply disruption. A mixed integer non-linear programming (MINLP) model is developed for order allocation considering different capacity, failure probability and quantity discounts for each supplier. We have shown that the formulated problem is NP-hard in nature and genetic al...

Abstract We consider a nonconvex mixed-integer nonlinear programming (MINLP) model proposed by Goldberg et al. (Comput Optim Appl 58:523–541, 2014. 10.1007/s10589-014-9647-y ) for piecewise linear function fitting. show that this MINLP is incomplete and can result in curve not the graph of function, because it misses set necessary constraints. provide two counterexamples to illustrate effect, p...

The problem of data reconciliation and the detection and identification of gross errors, such as measurement bias, are closely related and permits a solution within a mixed integer optimization framework. A mixed-integer linear programming (MILP) approach has been previously investigated by Soderstrom et al. (2001), where the process model was described by a set of linear equations. This paper ...

Significant advances have been made in the last two decades for the effective solution of mixed integer non-linear programming (MINLP) problems, mainly by exploiting the special structure of the problem that results under certain convexity assumptions. This paper discusses the computational experience with a novel decomposition algorithm which is based on the idea of closely approximating the f...