New Approach to Find Initial Basic Feasible Solution (IBFS) for Optimal Solution in Transportation Problem

Minimizing transportation time and getting optimal solutions are always considered as important factors while solving transportation problem. This paper shows a new approach for finding initial basic solution for transportation problem which reduces cost of transportation more than any transportation method such as LCM, northwest, Vogel’s approximation and so on. This method has been illustrated by taking an example;afterwards, it compares basic initial feasible solution with other methods IBF and optimal dictate solutions such as MODI and Steppingstone method.

A SUPERLINEARLY CONVERGENT SPLITTING FEASIBLE SEQUENTIAL QUADRATIC OPTIMIZATION METHOD FOR TWO-BLOCK LARGE-SCALE SMOOTH OPTIMIZATION

This paper discusses the two-block large-scale nonconvex optimization problem with general linear constraints.Based on the ideas of splitting and sequential quadratic optimization(SQO),a new feasible descent method for the discussed problem is proposed.First,we consider the problem of quadratic optimal(QO)approximation associated with the current feasible iteration point,and we split the QO into two small-scale QOs which can be solved in parallel.Second,a feasible descent direction for the problem is obtained and a new SQO-type method is proposed,namely,splitting feasible SQO(SF-SQO)method.Moreover,under suitable conditions,we analyse the global convergence,strong convergence and rate of superlinear convergence of the SF-SQO method.Finally,preliminary numerical experiments regarding the economic dispatch of a power system are carried out,and these show that the SF-SQO method is promising.

An improved multidisciplinary feasible method using DACE approximation approach

Multidisciplinary feasible method (MDF) is conventional method to multidisciplinary optimization (MDO) and well-understood by users. It reduces the dimensions of the multidisciplinary optimization problem by using the design variables as independent optimization variables. However, at each iteration of the conventional optimization procedure, multidisciplinary analysis (MDA) is numerously performed that results in extreme expense and low optimization efficiency. The intrinsic weakness of MDF is due to the times that it loop fixed-point iterations in MDA, which drive us to improve MDF by building inexpensive approximations as surrogates for expensive MDA. An simple example is presented to demonstrate the usefulness of the improved MDF. Results show that a significant reduction in the number of multidisciplinary analysis required for optimization is obtained as compared with original MDF and the efficiency of optimization is increased.

Homotopy Continuous Method for Weak Efficient Solution of Multiobjective Optimization Problem with Feasible Set Unbounded Condition

In this paper, we propose a homotopy continuous method (HCM) for solving a weak efficient solution of multiobjective optimization problem (MOP) with feasible set unbounded condition, which is arising in Economical Distributions, Engineering Decisions, Resource Allocations and other field of mathematical economics and engineering problems. Under the suitable assumption, it is proved to globally converge to a weak efficient solution of (MOP), if its x-branch has no weak infinite solution.

An Effective Approach to Determine an Initial Basic Feasible Solution: A TOCM-MEDM Approach

Transportation of products from sources to destinations with minimal total cost plays an important role in logistics and supply chain management. In this article, a new and effective algorithm is introduced for finding an initial basic feasible solution of a balanced transportation problem. Number of numerical illustration is introduced and optimality of the result is also checked. Comparison of findings obtained by the new heuristic and the existing heuristics show that the method presented herein gives a better result.

A Comparative Study of Initial Basic Feasible Solution by a Least Cost Mean Method (LCMM) of Transportation Problem

Transportation Problems (TP), as is known, are a basic network problem which can be formulated as a Linear Programming Problem (LPP). Transportation networks are built up in order to save transportation cost. In the solution procedure of a TP, finding an Initial Basic Feasible Solution (IBFS) is necessary to obtain the optimal solution. Optimality gives us the optimal route that prompts either most extreme benefit or least aggregate cost whichever is required. In this research paper, a new method named Least Cost Mean Method is proposed to obtain a better IBFS where row penalty and column penalty is brought out by the mean of lowest and next lowest cost of each row and each column of the cost matrix. The method is illustrated with numerical examples. To verify the performance of the proposed method, a comparative study is also carried out and observed that it is computationally easier and yielding comparatively better solution.

ON THE MINIMUM FEASIBLE GRAPH FOR FOUR SETS

Given a complete graph with vertex set X and subsets X_1, X_2,..., X_n, the problem of finding a subgraph G with minimum number of edges such that for every i = 1, 2,..., n G contains a spanning tree on X_i, arises in the design of vaccum systems. In general, this problem is NP-complete and it is proved that for n = 2 and 3 this problem is polynomial-time solvable. In this paper, we prove that for n = 4, the problem is also polynomial-time solvable and give a method to construct the corresponding graph.

Minimal feasible sets in variable resource constrained projects

To determine the reasonable resource dependent relations between activities for the purpose of exactly computing the total floats and the free floats of activities, correctly identifying critical activities and critical sequences in a project schedule with variable resource constraints, the concept of the minimal feasible set （MFS） is proposed and the properties of MFS are discussed. The methods to identify optimal MFSs and resource links are then studied. Furthermore, MFS is generalized to the situation that the preconditions of MFS are not satisfied. Contrastive results show that in establishing resource links and resolving floats, MFS is at least not inferior to other methods in all cases and is superior in most situations.

Feasible Research on ' Textile · Garment' Supply and Demand Interaction and Optimization Model

After China entries WTO, China's ‘ textile · garment'industry will confront the difficulties of growth and development. From the view of supply and demand interaction which is common in the social economy, this article analyzes the economic construction and character of China's ‘ textile · garment' industry, represented by Shanghai,Research shows that industrial construction backwardness hinders China's ‘ textile· garment' industry development, which features four bottlenecks in supply and demand interaction in ‘ textile· garment' industry.The key of optimizing the construction and quality of supply and denand interaction in ‘textile· garment'industry is to adjust industrial construction, break the bottlenecks, establish Shanghai as international fashion center, open middle and small size textile processing area with several levels, attach importance to scientific and technology creation and development combined with production, learning and research, and take part in domestic and international maket competition by high added value product, technology and marketing network.

Polyhedral Feasible Set Computation of MPC-Based Optimal Control Problems

Feasible sets play an important role in model predictive control(MPC) optimal control problems(OCPs). This paper proposes a multi-parametric programming-based algorithm to compute the feasible set for OCP derived from MPC-based algorithms involving both spectrahedron(represented by linear matrix inequalities) and polyhedral(represented by a set of inequalities) constraints. According to the geometrical meaning of the inner product of vectors, the maximum length of the projection vector from the feasible set to a unit spherical coordinates vector is computed and the optimal solution has been proved to be one of the vertices of the feasible set. After computing the vertices,the convex hull of these vertices is determined which equals the feasible set. The simulation results show that the proposed method is especially efficient for low dimensional feasible set computation and avoids the non-unicity problem of optimizers as well as the memory consumption problem that encountered by projection algorithms.

Exploration of Feasible Path for the“New Urbanization”in Practices

This paper introduced problems in the current construction of "new urbanization" from four perspectives, namely making new countryside planning, but not eliminating countryside, protecting architectural cultures, avoiding pursuit of grandiose western-style projects. In addition, solutions to the problems were proposed, the necessity and urgency of promoting new urbanization scientifi cally and reasonably was stressed, the feasible approach for the construction of new urbanization was explored.

Estimation of Attractive Regions of Nonlinear MPC Controller-A Feasible Solution-based Method

A new model predictive control(MPC) algorithm for nonlinear systems is presented,its stabilizing property is proved,and its attractive regions are estimated.The presented method is based on the feasible solution,which makes the attractive regions much larger than those of the normal MPC controller that is based on the optimal solution.

Feasible Teleportation Schemes with Five-Atom Entangled State

Teleportation schemes with a five-atom entangled state are investigated. In the teleportation scheme Bell state measurements （BSMs） are difficult for physical realization, so we investigate another strategy using separate measurements instead of BSM based on cavity quantum electrodynamics techniques. The scheme of two-atom entangled state teleportation is a controlled and probabilistic one. For the teleportation of the three-atom entangled state, the scheme is a probabilistic one. The fidelity and the probability of the successful teleportation are also obtained.

NONCONVEX FEASIBLE REGION OF HEAT EXCHANGER NETWORKS WITH UNCERTAIN STREAM PARAMETERS

A detailed study is carried out on the nonconvex feasible region of heat exchanger net-works with uncertain stream parameters.The new property of nonconvex feasible region——infeasiblehole property is revealed.By theoretical analysis to infeasible hole property,and combining with amethod of mathematical programming,the problem of flexibility analysis for the heat exchanger net-work with nonconvex feasible region can be solved more reasonably.

Study and realization of the computer support system on feasible reasoning and scientific decision-making of projects based on WEB

With the development of information technology, DSS can be used to resolve the complex process of the feasible reasoning and scientific decision-making of projects. This paper offers 7 exploiting principles for the computer support system on feasible reasoning and scientific decision-making of projects, that is, the principles of standardization, procedure, specification, agility, currency, practicability and development. On the basis of analysis on systematic procedure, the computer support system on feasible reasoning and scientific decision-making of projects is formed based on WEB, and its general structure, system function and the methods to be realized are introduced. The data composition of this system is analyzed following the principles of integrality, development, perspicuity and consistency. Also, the model-base management system is designed for the management of model storage and management of model operation.

New Procedure of Finding an Initial Basic Feasible Solution of the Time Minimizing Transportation Problems

Minimization of transportation time is a great concern of the transportation problems like the cost minimizing transportation problems. In this writing, a transportation algorithm is developed and applied to obtain an Initial Basic Feasible Solution (IBFS) of transportation problems in minimizing transportation time. The developed method has also been illustrated numerically to test the efficiency of the method where it is observed that the proposed method yields a better result.

A SUPERLINEARLY AND QUADRATICALLY CONVERGENT SQP TYPE FEASIBLE METHOD FOR CONSTRAINED OPTIMIZATION

A new SQP type feasible method for inequality constrained optimization is presented,it is a combination of a master algorithm and an auxiliary algorithm which is taken only in finite iterations.The directions of the master algorithm are generated by only one quadratic programming, and its step\|size is always one, the directions of the auxiliary algorithm are new “second\|order” feasible descent. Under suitable assumptions,the algorithm is proved to possess global and strong convergence, superlinear and quadratic convergence.

Metallic nanoparticles for peripheral nerve regeneration: is it a feasible approach?

The primary function of the peripheral nerves is to transmit signals from the spinal cord to the rest of the body,or to convey sensory information from the rest of the body to the spinal cord.In case of injury or a health disorder,this pathway can be partially or totally disrupted,resulting in pain,loss of sensation,reduced muscular strength,poor coordination,or complete paralysis.

Feasible Study for Nanhai Petrochemical Project Accomplished

It is expected that a total of 5 billion US dollars will be invested in Nanhai Petrochemical Project,the largest Chinese-foreign equity joint venture(JV)in petrochemical industry of south part of China,which includes 50%from Shell a and 50%from Chinese party.The investment of the Chinese party is comprised of 20%from CNOOC,10%separately from Sinopech,Guangdong pro-vince,Bureau of Business Promotion.

Multi-Objective Genetic Algorithm to Design Manufacturing Process Line Including Feasible and Infeasible Solutions in Neighborhood

This paper treats multi-objective problem for manufacturing process design. A purpose of the process design is to decide combinations of work elements assigned to different work centers. Multiple work elements are ordinarily assigned to each center. Here, infeasible solutions are easily generated by precedence relationship of work elements in process design. The number of infeasible solutions generated is ordinarily larger than that of feasible solutions generated in the process. Therefore, feasible and infeasible solutions are located in any neighborhood in solution space. It is difficult to seek high quality Pareto solutions in this problem by using conventional multi-objective evolutional algorithms. We consider that the problem includes difficulty to seek high quality solutions by the following characteristics： （1） Since infeasible solutions are resemble to good feasible solutions, many infeasible solutions which have good values of objective functions are easily sought in the search process, （2） Infeasible solutions are useful to select new variable conditions generating good feasible solutions in search process. In this study, a multi-objective genetic algorithm including local search is proposed using these characteristics. Maximum value of average operation times and maximum value of dispersion of operation time in all work centers are used as objective functions to promote productivity. The optimal weighted coefficient is introduced to control the ratio of feasible solutions to all solutions selected in crossover and selection process in the algorithm. This paper shows the effectiveness of the proposed algorithm on simple model.