فهرست مطالب ghasem moslehi

Operating rooms have become the most important areas in hospitals because of the scarcity and cost of resources. The present study investigates operating room scheduling and rescheduling considering the priority of surgical patients in a specialized hospital. The ultimate purpose of scheduling is to minimize patient waiting time, surgeon idle time between surgeries, and penalties for deviations from operating room preferences. A mathematical programming model is presented to solve the problem. Because the problem is strongly NP-hard, two heuristic algorithms are presented. A heuristic algorithm based on a mathematical programming model with local search obtains near-optimal solutions for all the samples. The average relative deviation of this algorithm is 0.02%. In continuous, heuristic algorithms performance have been investigated by increasing the number of patients and reduce the number of recovery beds. Next, a rescheduling heuristic algorithm is presented to deal with real-time situations. This algorithm presents fewer changes resulting from rescheduling in comparison with the scheduling problem.

In recent years, significant energy consumption and facing global warming have led to concern worldwide. Therefore, governments have turned to deterrent actions such as imposing daily tariffs in different intervals to tackle energy consumption. This article addresses unrelated parallel machine energy-efficient scheduling problems by considering sequence-independent setup times and energy consumption tariffs. The objective function is that jobs should be assigned to machines and processed in different intervals so that the cost of consumed energy becomes as less as possible. It should be noted that the assumed sequence-independent setup times are addressed in two different modes, setup times jointed to processing time and setup times disjointed from processing time. Design/methodology/approach: To optimize the total energy consumption cost in unrelated parallel machine scheduling problems with sequence-independent setup times jointed to processing time and disjointed from processing time, mixed-integer linear programming (MILP) models have been proposed from two different points of view. The first model has been formulated according to the predecessor jobs of a special job, while the second model has been conducted based on the immediate predecessor job. Also, a fix and relax heuristic (FRH) algorithm has been conducted to solve large- scale instances. All mathematical models and the heuristic algorithm have been coded in the Visual C# 2017 environment and implemented using the CPLEX 12.8 Concert Technology on a PC with 32GB RAM and Intel Corei7 4.0 GHz CPU (4 cores). Also, a sizeable number of instances have been solved to evaluate the efficiency of mathematical models and the heuristic algorithm and to ensure their accuracy.

According to numerical analysis, both mathematical models solved the instances of up to 20 jobs and 80 machines optimally for sequence-independent setup-times jointed to processing time, and sequence-independent disjointed from processing time problems. However, generally speaking, the mathematical model based on predecessor jobs was more efficient than another mathematical model, especially in terms of run time. Moreover, the proposed fix and relax-based heuristic algorithm solved instances of up to 20 machines and 190 jobs for the disjointed setup times problem, and up to 20 and 220 instances for the jointed setup times problem. It should be noted that all instances were generated analogously to the literature.

A vast number of exogenous factors contributed to the scheduling problems in the real world, which can disturb the scheduling process easily, frequent power outages, machine breakdown, and operator absence. Besides, considering all the real world's possibilities raises extreme complexity in problems. Therefore, similar to other studies, some assumptions were considered as follows: - machines are always available at all times; - idle is allowable for machines; - the energy consumption rate of various machines is different for each job; - each machine's energy consumption rate during processing and setups is different for each job, it is assumed as constant; - preemption is not allowed in the job's processing and setups; - all jobs are available at the beginning of the planning horizon; and - each machine can process or do the setup for only one job at a time.

Given that unrelated parallel machines are one of the most practical scheduling environments, this article can be effective in production sites and operation lines that contain such a kind of machine. Besides, unrelated parallel machines cover identical and related parallel machines. Consequently, this paper is the building blocks of cost-effective and environmentally friendly scheduling programs. Also, the application of unrelated parallel machines is not merely restricted to production problems. In other words, unrelated parallel machine scheduling problems can be used in other real-world cases, such as airplane scheduling and elevator scheduling. Originality/value - In this paper, unrelated parallel machine energy-efficient scheduling has been addressed considering sequence-independent setup times. Since it was a common belief that sequence-independent setup times could be included in processing times, sequence-independent setup times have been neglected so far. However, in this innovative study for the first time, an unrelated parallel machine energy efficient problem was investigated with sequence-independent setup times. Mathematical programming models and a heuristic algorithm were proposed for such a practical problem.

The routing and loading problems are two essential issues to reduce transportation costs. In the recent decade, these problems have been integrated to realize the vehicle routing problem. Failure to comply with the loading constraints may result in damage to the goods or less use of the vehicle space, which in each case will result in additional damage and cost. In this paper, for the first time, the integrated routing problem of pickup, delivery, and backhaul with three-dimensional loading constraints and time window is considered, where the constraints of accumulation, orientation, non-reloading, and multi-delivery conditions are examined. In this study, items and containers are considered heterogeneous. By examining the subject literature, this problem was not observed in the literature. A mixed-integer programming model, a heuristic algorithm, and two metaheuristic algorithms based on tabu search and variable neighborhood search are proposed for this problem. For small instances the proposed metaheuristics were compared to the lower bound obtained from relaxing some constraints of the model. For large instances, the two metaheuristic algorithms are compared together. The results show that the average percentage of relative error in the tabu search and variable neighbor search algorithms is 0.96 and 0.88, respectively. Also, the tabu search algorithm and variable neighborhood search were able to give better results out of 54 instances in 27 and 25 instances, respectively.

In single machine scheduling problems with availability constraints, machines are not available for one or more periods of time. In this paper, we consider a single machine scheduling problem with flexible and periodic availability constraints. In this problem, the maximum continuous working time for each machine increases in a stepwise manner with two different values allowed. Also, the duration of unavailability for each period depends on the maximum continuous working time of the machine in that same period, again with two different values allowed. The objective is to minimize the number of tardy jobs. In the first stage, the complexity of the problem is investigated and a binary integer programming model, a heuristic algorithm and a branch-and-bound algorithm are proposed in a second stage. Computational results of solving 1680 sample problems indicate that the branch-and-bound algorithm is capable of not only solving problems of up to 20 jobs but also of optimally solving 94.76% of the total number of problems. Based on numerical results obtained, a mean average error of 2% is obtained for the heuristic algorithm.

This paper addresses the Tardy/Lost penalty minimization on a single machine. According to this penalty criterion, if the tardiness of a job exceeds a predefined value, the job will be lost and penalized by a fixed value. Besides its application in real world problems, Tardy/Lost measure is a general form for popular objective functions like weighted tardiness, late work and tardiness with rejection and hence, the results of this study are applicable for them. Initially, we present two approximation algorithms. Then, two special cases of the main problem are considered. In the first case, all jobs have the same tardiness weights where an FPTAS is developed using the technique of “structuring the execution of an algorithm". The second special case occurs when none of the jobs can be early. For this case, a 2-approximation algorithm is developed as well as a dynamic programming algorithm which is converted to an FPTAS.

In competitive markets, attracting potential customers and keeping current customers is a survival condition for each company. So, paying attention to the requests of customers is important and vital. In this paper, the problem of order acceptance and scheduling has been studied, in which two types of customers or agents compete in a single machine environment. The objective is maximizing sum of the total profit of first agent's accepted orders and the total revenue of second agent. Therefore, only the first agent has penalty and its penalty function is lateness and the second agent's orders have a common due date and this agent does not accept any tardy order. To solve the problem, a mathematical programming, a heuristic algorithm and a pseudo-polynomial dynamic programming algorithm are proposed. Computational results confirm the ability of solving all problem instances up to 70 orders size optimally and also 93.12% of problem instances up to 150 orders size by dynamic programming.

This paper addresses the Tardy/Lost penalty minimization with common due dates on a single machine. According to this performance measure, if the tardiness of a job exceeds a predefined value, the job will be lost and penalized by a fixed value. Initially, we present a 2-approximation algorithm and examine its worst case ratio bound. Then, a pseudo-polynomial dynamic programming algorithm is developed. We show how to transform the dynamic programming algorithm to an FPTAS using the technique of "structuring the execution of an algorithm" and examine the time complexity of our FPTAS.

Increasing competition in the air transport market has intensified active airlines’ efforts to keep their market share by attaching due importance to cost management aimed at reduced final prices. Crew costs are second only to fuel costs on the cost list of airline companies. So, this paper attempts to investigate the cockpit crew pairing problem. The set partitioning problem has been used for modelling the problem at hand and, because it is classified in large scale problems, the column generation approach has been used to solve LP relaxation of the set partitioning model. Our focus will be on solving the column generation sub-problem. For this purpose, two algorithms, named SPRCF and SPRCD, have been developed based on the shortest path with resource constraint algorithms. Their efficiency in solving some problem instances has been tested and the results have been compared with those of an algorithm for crew pairing problem reported in the literature. Results indicate the high efficiency of the proposed algorithms in solving problem instances with up to 632 flight legs in a reasonable time.

In this paper, minimizing the number of tardy jobs in two-machine flowshop scheduling with non-simultaneous job entrance is discussed. It is proven that the complexity of the problem is NP_hard. Therefore, a heuristic algorithm is proposed to solve the large scale problems. Besides, an exact branch and bound algorithm with utilizing heuristic algorithm as upper bound proposed to achieve optimal solution. Computational results demonstrate that branch and bound method solves problems with 28 jobs in the set High and 20 jobs in the set Low in a reasonable time. Results show the capability of the proposed upper bound, lower bounds and dominance rules. Also, it is shown that the average ratio of optimal solution to the heuristic one with the objective ∑(1-Ui) is at most 1.11 which is smaller in contrast with other researches in the literature. This ratio proves efficacy of the proposed heuristic algorithm. Finally, according to efficiency of the presented approach, sample problems with large dimensions were solved and their results were displayed.

Considering its application, stochastic lot sizing is a significant subject in production planning. Also the concept of service level is more applicable than shortage cost from manager's viewpoint. In this paper, the stochastic multi period multi item capacitated lot sizing problem has been investigated considering service level constraint. First, the single item model has been developed considering service level and with no capacity constraint and then, it has been solved using dynamic programming algorithm and the optimal solution has been derived. Then the model has been generalized to multi item problem with capacity constraint. The stochastic multi period multi item capacitated lot sizing problem is NP-Hard, hence the model could not be solved by exact optimization approaches. Therefore, simulated annealing method has been applied for solving the problem. Finally, in order to evaluate the efficiency of the model, low level criterion has been used.

In this paper, we propose an iterated greedy algorithm for solving the blocking flow shop scheduling problem with total flow time minimization objective. The steps of this algorithm are designed very efficient. For generating an initial solution, we develop an efficient constructive heuristic by modifying the best known NEH algorithm. Effectiveness of the proposed iterated greedy algorithm is tested on the Taillard''s instances. Computational results show the high efficiency of this algorithm with comparison state-of-the-art algorithms. We report new best solutions for 88 instances of 120 Taillard''s instances.

Nowadays, scheduling problems have a considerable application in production and service systems. In this paper, we consider the scheduling of n jobs on a single machine assuming no machine idleness, non-preemptive jobs and equal process times. In many of previous researches, because of the delivery dalays and holding costs, earliness and tardiness penalties emerge in the form of linear combinations in objective functions. However, minimizing the weighted quadratic earliness and tardiness penalties is considered in this paper. A branch and bound algorithm including some dominance rules, lower bounds and upper bounds is proposed to solve the problem. Finally, the efficiency of proposed method is proved via some test problems.

Self assessment is an interesting subject for all managers, especially for the managers of incubators. The incubator performance assessment by indexes (IPAI) is a simple, interesting and effective method for measuring the performance index of an incubator. The system is based on changing the scope of performance of several indicators to fixed scales (metrics), weighing them and combining them. Strategic evaluation is basically consists of three basic activities which are investigating the principles of the companies or organizations strategies, comparing the ideal and real results and making improvements. This paper focuses on the second part to make sure that the performance adjusts correctly with the planning programs. This paper is going to introduce an index for measuring and assessing the level of technology improvement in Isfahan Science and Technology Town (ISTTs) Incubator and Science Park. It also addresses the methodology used for these calculations. Measuring the indicators for ISTTs incubator will be discussed at the final part of this paper as a case study.

We are living in a world where the complexity of cause and effect relations is in a continuous increase. The owners of the new ideas, their supporters and the beneficiaries encounter different questions for starting a new business activity. The questions such as Will this idea become successful or not? or What kinds of supports and considerations are necessary for this idea to be successful? are some examples. The idea assessment process is an important and interesting subject for both innovators and incubators managers so that it make the former familiar with the probable strengths and weaknesses and for the latter i.e. the managers of incubators the significance is in admitting the owners of ideas in incubators and starting to support them based on their needs in the early stages of the innovation process. The Innovation Development Early Assessment System has been developed for the assessment of the possibility of commercializing the ideas in the early stages of innovation. This paper will introduce this system and it further addresses the method of improving and developing it as a tool in the hands of the incubators managers helping them in the admission process of companies and helping them to recognize the support services required by their tenants during their residency in the incubator. It will also look at this system as a tool for making the owners of ideas familiar with the probable barriers and obstacles that may lead to their failure. The improvement method proposed for this system has been defined with regard to the existing conditions of the applicants of settlement in the incubator. A case study and the analysis of the results obtained through this system will come at the final part of this paper.

Incubators have gained wide reputation in most countries as efficient institutions contributing to regional development and economic growth. They assist their clients through their value-adding services and a wide range of support services and facilities that cannot be easily procured from other sources. The content of these services and the way they are supplied will have important effects on the success of the incubators, and thereby, on the incubators’ performance. Introducing improved incubation models, informing incubators of their distance from acceptable performance norms and models, and disseminating incubators’ success stories among those involved in the industry will be tools that are expected to assist incubator managers to make more informed and enlightened decisions. The use of composite indicators is a simple method of comparing a wide variety of systems under evaluation such as countries and organizations dealing with a multitude of complicated and wide issues including environmental, economic, social, and technological. Normally, the main objective in defining composite indicators is to compare the performance of a group of subjects evaluated along a given dimension. These indicators can also function as useful tools in analyzing policies and in communication of information to the public. In this paper, first, a state-of-the-art account of constructing composite indicators will be presented and then a number of tentative composite indicators will be introduced. Special emphasis will be laid on key performance indicators used in ranking technology incubators with due regard to the Iranian business incubation environment. This study is the first of its kind and is expected to open new avenues to taking effective measures in improving business and technology incubation programs.