in this paper, a new approach to overlapping operations in job shop scheduling is presented. in many job shops, a customer demand can be met in more than one way for each job, where demand determines the quantity of each finished job ordered by a customer. in each job, embedded operations can be performed due to overlapping considerations in which each operation may be overlapped with the other...

this study aims to deal with a more realistic combined problem of project scheduling and material ordering. the goal is to minimize the total material holding and ordering costs by determining the starting time of activities along with material ordering schedules subject to some constraints. the problem is first mathematically modelled. then a hybrid simulated annealing and genetic algorithm is...

this study aims to minimize the total cost of a four-echelon supply chain including suppliers, an assembler, distributers, and retailers. the total cost consists of purchasing raw materials from the suppliers by the assembler, assembling the final product, materials transportation from the suppliers to the assembler, product transportation from the assembler to the distributors, product transpo...

earth dam is a structure as homogeneous or non-homogeneous forms for raising water level or water supply. earth dam consist of different parts that one of the main parts is clay core. choosing an optimal non permeable core which causes reduction of seepage through dam body and also being stable is necessary. the objective of this research is to optimize the geometry of earth dam clay core such ...

We consider a special type of dimensionality reduction classification problem where the decision-making objective is to minimize misclassification cost and attributes (MMCA). We propose a two-stage solution approach for solving the MMCA problem. Using simulated data sets and different misclassification cost matrices, we test our two-stage exhaustive and simulated annealing procedures. Our resul...

Metaheuristics are general problem solving algorithms which abstract from the actual problem description. Therefore they can be easily applied to many optimization problems. Simulated annealing is a simple and fast metaheuristic with an analogy to metal processing. As metal particles generate a solid and regular structure when cooling slowing simulated annealing seeks a low-energy solution avoi...

Simulated annealing is a well-studied local search metaheuristic used to address discrete and, to a lesser extent, continuous optimization problems. The key feature of simulated annealing is that it provides a mechanism to escape local optima by allowing hill-climbing moves (i.e., moves which worsen the objective function value) in hopes of finding a global optimum. A brief history of simulated...

A bi-objective mathematical model is developed to simultaneously consider the quay crane and yard truck scheduling problems at container terminals. Main real-world assumptions, such as quay cranes with non-crossing constraints, quay cranes’ safety margins and precedence constraints are considered in this model. This integrated approach leads to better efficiency and productivity at container te...

This paper presents the investigation of an evolutionary multi-objective simulated annealing algorithm with variable neighborhoods to solve the multi-objective multicast routing problems in telecommunications. The hybrid algorithm aims to carry out a more flexible and adaptive exploration in the complex search space by using features of the variable neighborhood search to find more non-dominate...