Liu Shi-xin

An Agent-based Evolutionary Search for Dynamic Travelling Salesman Problem

This paper presents an agent-based evolutionary search algorithm (AES) for solving dynamic travelling salesman problem (DTSP). The proposed algorithm uses the principal of collaborative endeavor learning mechanism in which all the agents within the current population co-evolve to track dynamic optima. Moreover, a local updating rule which is much the same of permutation enforcement learning scheme is induced for diversity maintaining in dynamic environments. The developed search algorithm and benchmark generator are then built to test the evolutionary model for dynamic versions of travelling salesman problem. Experimental results demonstrate that the proposed method is effective on dynamic problems and have a great potential for other dynamic combinatorial optimization problems as well.

A new method to solve project scheduling problems with multi-skilled workforce constraints

With the developing of technology and economic of society, skilled workforce has been playing as the key role through the trend of prosperity. Project scheduling problems with multi-skilled workforce constraints (PSPMSWC) have become a research hotpot in the field of human resource allocation and project scheduling. Following the description and model of the PSPMSWC, a hybrid Benders decomposition (HBD) algorithm is presented in detail as well as the scheme of total solving process with heuristic inferring. After the programming and solving operation, results are gathered and analyzed afterward with conclusion at last.

Combined heuristics for determining order quantity under time-varying demands

Abstract The time-varying demands for a certain period are often assumed to be less than the basic economic order quantity (EOQ) so that total replenishment quantity rather than economic order quantity is normally considered by most of the heuristics. This acticle focuses on a combined heuristics method for determining order quantity under generalized time-varying demands. The independent policy (IP), abnormal independent policy (AIP) and dependent policies are studied and compared. Using the concepts of normal/abnormal periods and the properties of dependent policies, a dependent policy-based heuristics (DPH) is proposed for solving the order quantity problems with a kind of time-varying demands pattern under which the first period is normal. By merging the Silver-Meal (S-M) heuristics and the dependent policy-based heuristics (DPH), a combined heuristics (DPH/S-M) is developed for solving order quantity problems with generalized time-varying demands. The experimentation shows that (1) for the problem with one normal period, no matter which position the normal period stands, the DPH/S-M could not guarantee better than the S-M heuristics, however it is superior to the S-M heuristics in the case that the demands in the abnormal periods are in descending order, and (2) The DPH/S-M is superior to the S-M heuristics for problems with more than one normal period, and the more the number of normal periods, the greater the improvements.

An object-oriented methodology for solving the RCPSPs with heuristics and metaheuristics

Because various heuristics and metaheuristics have been proposed to solve the well known NP-hard, resourceconstrained project scheduling problem (RCPSP), it is currently difficult to compare the computational efficiency of these heuristics implemented on different computers where, in addition, the computer codes may have been written in different computer languages. This problem is solved when all relevant heuristics can be applied within the framework of a single computer program. By use of the object-oriented programming (OOP) methodology, we developed a general software framework for the heuristics and metaheuristics for solving the RCPSP. Currently this includes six heuristics and two metaheuristics. The framework of the software allows a more advanced user to append more effective heuristics and play around with several parameters of these metaheuristics with a bare minimum of coding effort.

Models for coal blending with inventory in coal-fired power plant

Coal blending technology has attracted much attention in coal-fired power plant of China, especially used to solve the conflict of actual supplied coal and designed coal in the boiler. According to blending schemes and relations between single coal and blending coal used in the factory, this paper formulates a resource-constrained 0-1 mixed integer programming model considering inventory by using the minimum coal blend costs as the objective function. This model determines the proportion of each component coal that is in a ton of the optimum coal blend. In addition, all coal quality parameters calculated by linear constraints in the coal blend should be within the range of given border. Finally, we get the optimum solutions of the model by setting different inventory problems and prices of each single coal in the CPLEX software. The results provide a good reference for coal blending.

An approach to establish and evaluate pricing business process in electronic commerce

There are a lot of illogical factors in traditional pricing business process, such as low level of information, automation and poor net, which decrease pricing efficiency, especially in electronic commerce. To solve this problem, traditional pricing business process is analyzed, valued and reengineered with a method of business process quantitative analysis based on process algebra. Then a new pricing business process that is suitable for electronic commerce environment is established according to the principles of business process reengineering and the characteristics of pricing in electronic commerce environment. The evaluation criterions before and after process reengineering are investigated, and the results are satisfied. The results verify that the methods are practical.

Dynamic pricing model of digital knowledge commodity considering competition from congener commodity

The distinctive characteristics of digital knowledge commodity (DKC) make its pricing method different from traditional commoditypsilas. One hand, cost characteristic of DKC gives us more price choices. On the other hand, characteristics else of DKC bring us more difficulties to price. To solve this problem, the first-degree price discrimination is adopted, with respect to the stage in which the on-line sellerpsilas sale number does not exceed critical sale number. Then dynamic pricing model considering competition from congener commodity is built, in which commodity copyright cost, advertisement cost, competitorpsilas price, customerpsilas expectation of commodity and customer behavior are considered, for the sake of maximizing the sale and the profit of an on-line seller. In customer behavior model, the positive exterior influence of Web on customer purchase behavior is considered, and the influence of commodity brand, history sale number and price are quantized.

Modeling for project scheduling with multi-skilled workforce constraints and uncertainty

This paper presents a new workforce allocation optimization model for project scheduling problems with multi-skilled workforce constraints (PSPMSWC), under uncertainty about the projects. The model is a mixed-integer program(MIP) model that aims at maximizing the total profit. As a subproblem, scheduling and staff assignment for projects must also be optimized. In the experiment, projects are selected randomly, and we get the workforce allocation optimal solution as well as workforce assigned optimal strategy by means of CPLEX.

Timed Petri net based optimization approach for selective disassembly lot sizing

On the basis of analyzing the basic information of single type of product and constraint relations between parts and components, the constraint relations are showed by Petri net model, in which we introduce the factors of time and resources into places and transitions. This paper proposes lot sizing selective disassembly optimization problem based on timed Petri net with consideration of multi-resources constraints, establishes a mathematical model of this problem aims at minimization of disassembly time, solves the model with CPLEX software, and verifies the effectiveness of this model in solving this type of disassembly optimization problem through the disassembly example of silicon oil fan and several randomly generated problem instances.