CN107808210A - The dismantlement scheme of Complex Product dismounting regeneration and the Integrated Decision method of regeneration scheme - Google Patents

The dismantlement scheme of Complex Product dismounting regeneration and the Integrated Decision method of regeneration scheme Download PDF

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CN107808210A
CN107808210A CN201710821870.9A CN201710821870A CN107808210A CN 107808210 A CN107808210 A CN 107808210A CN 201710821870 A CN201710821870 A CN 201710821870A CN 107808210 A CN107808210 A CN 107808210A
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regeneration
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楼佩煌
郭大宏
钱晓明
孟凯
武星
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Nanjing University of Aeronautics and Astronautics
Miracle Automation Engineering Co Ltd
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Miracle Automation Engineering Co Ltd
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Abstract

The present invention discloses a kind of dismantlement scheme of Complex Product dismounting regeneration and the Integrated Decision method of regeneration scheme, step are as follows：The dismantlement scheme and regeneration scheme of the initial complicated product to be removed of random generation；According to complicated product component quality state to be removed and dismounting dominance relation, feasible dismantlement scheme and regeneration scheme are generated；Dismantlement scheme and regeneration scheme are encoded using real coding mechanism；Evolutional operation is carried out to above-mentioned coding using improved Cooperative Evolutionary Algorithm, optimizes overall regeneration value, while draw optimal dismantlement scheme and regeneration scheme.Integrated Decision method proposed by the present invention, existing method is overcome because can not while considering dismantlement scheme and influencing each other for regeneration scheme not realize benefit the shortcomings that, realize the Integrated Decision of complex product dismounting regeneration.

Description

The dismantlement scheme of Complex Product dismounting regeneration and the Integrated Decision of regeneration scheme Method
Technical field：
The present invention relates to waste product recycle applications technical field, is dismantled again more particularly, to a kind of Complex Product Raw dismantlement scheme and the Integrated Decision method of regeneration scheme.
Background technology：
The mode of waste product recycle applications mainly includes：Material recycles, spare parts remanufacture and direct profit again With etc..The mode of recycle applications is rationally determined, the overall regeneration value of waste product can be effectively improved.Remanufacture in directly again Using being by improving one of effective means that its recovery reuses added value to the reparation of waste product high-tech and transformation.And tear open The key precondition link for being product remanufacturing and directly recycling is unloaded, Disassembly layout is believed according to product structure, assembly relation etc. Breath, lower some or certain several components (such as valuable parts, poisonous or damage parts) specified, generation are dismantled from product Meet the target element disassembly sequence of certain constraints, to reduce take-down time and cost, improve operating efficiency.
With the raising of studied waste product complexity, tend to be absorbed in using traditional planing method and " combine quick-fried It is fried ", and the problem of traditional decision-making technique generally only considers Disassembly layout, do not consider dismantlement scheme planning and regeneration side simultaneously Case selection influences each other, it is difficult to realizes the maximization of recycle applications benefit.Chinese invention patent application number is 200910155247.X, entitled " the complex product target and cooperation disassembly planing method of supporting Green design " are absorbed in zero The complete Disassembly layout of part, and do not account for regeneration scheme.Document " Zhang Xiufen, Zhang Shuyou, Yi Guodong, waits towards complicated machinery The target selectivity disassembly sequence planning method [(periodical) mechanical engineering journal] of product, the o. 11th of volume 2010,46,172- 178 " propose a kind of method dismantled combination chart and particle cluster algorithm and be combined that proposes, the dismounting of solving complexity engineering goods is deep Degree and disassembly sequence, but do not account for the recycle applications processing mode of parts." Zhang Xiufen, Zhang Shu have to be based on to document The detaching products Sequence Planning method [(periodical) computer integrated manufacturing system] of particle cluster algorithm, the 3rd phase of volume 2009,15, 508-514 " establishes a kind of detaching products and assigns power mixing graph model, and produces detachable sequence by the method for geometric reasoning, Document " Liu Zhifeng, disassembly sequence planning [(periodical) Hefei of Yang Dejun, Gu Guogang based on simulated annealing particle swarm optimization algorithm Polytechnical university's journal natural science edition], the 2nd phase of volume 2011,34,161-165 " constructs product structure based on disassembly constraint graph Expression model, and carry out disassembly sequence planning, document " Wang Junfeng, Li Shiqi, Liu Ji using simulated annealing particle swarm optimization algorithm The product selection dismantling technology research [(periodical) computer integrated manufacturing system] of red Oriented Greens manufacture, volume 2007,13 the 6 phases, 1097-1102 " propose the product selection Disassembly layout method based on ant group algorithm, give the production towards selection dismounting Product figure models and the dynamic construction process of selection disassembly sequence, and still, the studies above and institute's extracting method do not account for dismounting deeply Spend the select permeability of decision-making and parts recycle applications processing mode.For above-mentioned deficiency, it is proposed that Integrated Decision problem, And consider dismantlement scheme and regeneration scheme simultaneously for problematic features, devise dismantlement scheme and regeneration scheme Integrated Decision side Method.
The content of the invention：
It is an object of the invention to provide the collection of a kind of dismantlement scheme of Complex Product dismounting regeneration and regeneration scheme Into decision-making technique, the dismantlement scheme and regeneration scheme of complicated product to be removed are randomly generated, according to complicated product zero to be removed Part quality state and dismounting dominance relation, to above-mentioned dismantlement scheme and regeneration scheme amendment；Using real coding mechanism to dismounting Scheme and regeneration scheme coding；Evolutional operation is carried out to above-mentioned coding using improved Cooperative Evolutionary Algorithm, optimizes overall regeneration Value；Determine complex product optimal dismantlement scheme and regeneration scheme simultaneously.
The present invention adopts the following technical scheme that：The dismantlement scheme of Complex Product dismounting regeneration a kind of and regeneration scheme Integrated Decision method, step are as follows：
Step 1：The dismantlement scheme and regeneration scheme of the initial complicated product to be removed of random generation；
Step 2：According to complicated product component quality state to be removed and dismounting dominance relation, feasible dismounting is generated Scheme and regeneration scheme；
Step 3：Dismantlement scheme and regeneration scheme are encoded using real coding mechanism；
Step 4：Evolutional operation is carried out to above-mentioned coding using improved Cooperative Evolutionary Algorithm, optimizes overall regeneration value, Draw optimal dismantlement scheme and regeneration scheme simultaneously；
Further, feasible dismantlement scheme and regeneration scheme are generated in step 2, is comprised the following steps that：
Step 1：The initial random regeneration scheme of generation and dismounting weight set；
Step 1.1：A regeneration scheme is randomly assigned to each part；
Step 1.2：Each part is distributed one 1 and uniquely dismantles weight as the part to unduplicated certificate n；
Step 2：Generate feasible regeneration scheme；
Step 2.1：The regeneration scheme of each part is checked, is revised as at random if program technology is infeasible feasible Regeneration scheme；
Step 2.2：When exist part be assigned to recycle when, if it is died of old age quality level be unsatisfactory for recycle minimum Quality level, then the part regeneration scheme is changed as recycling or is remanufactured；
Step 2.3：The regeneration rate of new regeneration scheme is checked, if regeneration rate is unsatisfactory for minimum threshold, randomly chooses one Individual regeneration scheme is the part of recycling, and its scheme is changed to remanufacture；
Step 2.4：If be still unsatisfactory for regenerate rate requirement, repeat step 2.3, otherwise, obtained one it is feasible Regeneration scheme, continue executing with step 3；
Step 3：By inversely traveling through the minimal set dismantled preferential figure and generate part to be torn open；
Step 3.1：The regeneration scheme of each part is traveled through, if the part will be remanufactured or recycled, by part Minimum dismounting set is added, if part contains poisonous and harmful substances, the part is equally added into minimum dismounting set, thus obtained initial Minimum dismounting set；
Step 3.2：The direct precursor set of each part, is to work as if there is a part in the minimum dismounting set of traversal The direct precursor of preceding traversal part, and the part is then also added into minimum dismounting set without minimum dismounting set is added, by This obtains the minimum dismounting set corresponding to regeneration scheme；
Step 4：Local topology figure corresponding to the minimum dismounting set of structure；
Step 4.1：Dismounting precedence relation matrix corresponding to the minimum dismounting set of generationIf all parts are all Need to dismantle, be then dismounting completely, directly perform step 5；Otherwise to any two part u, v in minimum dismounting set, if u It is v direct precursor, then makesOtherwise it is 0；
Step 4.2：A local topology figure PTG={ V, E } is built, wherein V is the vertex set for representing each part, E It is the side for representing removing relation；
Step 4.3：Calculate the I that becomes a mandarin of each node in local topology figureu, IuReflect total of part u direct precursors Number；
Step 5：Feasible disassembly sequence is generated based on dismounting weight and topological sorting method；
Step 5.1：Any one is without the part (I for directly dismantling forerunneru=0) can directly dismantle, search is current Demountable part node forms S in figuredIf the gesture of the set | Sd|=0, represent without dismountable part, computing Stop；If | Sd|=1, then the part is directly added into disassembly sequence set；If | Sd| ＞ 1, then according to dismounting weight to it In part carry out descending arrangement, and according to this by these parts add disassembly sequence；
Step 5.2：Delete and added in local topology figure PTG corresponding to the node and these parts of disassembly sequence set Side, update remaining node in PTG and become a mandarin；
Step 5.3：If local topology figure is not skyStep 5.1 is then repeated, otherwise stops computing, When having traveled through node all in local topology figure PTG, then a feasible dismantlement scheme has obtained, and then, obtain complete Feasible solution.
Further, the real coding mechanism in step 3, each gene represents part in regeneration scheme individual Regeneration scheme, 1 represents material recycling, and 2 represent and remanufacture, and 3 represent and directly recycle, disassembly sequence n part of individual It is random to dismantle weighted value to represent.
Further, it is as follows the step of improved Cooperative Evolutionary Algorithm in step 4：
Step 1：Initialization of population, regeneration scheme, i.e. randomizing scheme and random weight recombination are initialized, checks regeneration scheme Feasibility, and repair be feasible regeneration scheme；
Step 2：The initial fitness of individual is calculated respectively, to each feasible global solution, calculates its recycling profit, dismounting Cost and net profit, herein using net profit value as fitness evaluation value；
Step 3：Build the neighborhood of Local Interaction search；
Step 4：Symbiosis cooperation and competition operates, each individual selected in the neighborhood of another population one it is random Individual is used as symbiotic partner；Then, calculate each individual fitness i.e. target function value in the two neighborhoods and confirm current office Portion's adaptive optimal control degree, then evaluate each individual fitness and confirm local optimum fitness in the neighborhood；If greater than original Fitness, then substitute an inferior solution at random with the gene of optimal solution；
Step 5：Genetic evolution, individual in each neighborhood is selected, intersected and mutation operation produces new son individual, and Replace the poor individual in original seed group；
Step 6：Elite solution local strengthening is searched for；
Step 7：Evolve and stop judging, if having reached greatest iteration number, stop, otherwise repeat step 3；
Step 8：Global perturbation strategy, if the continuous g of locally optimal solutionBIn generation, does not update, then with certain probability to part Worst individual carries out disturbing operation and renewal, to increase the diversity of population, goes to and performs step 3.
The present invention has the advantages that：
1. a pair random regeneration scheme is repaired, and proposes that a kind of multiple target backward induction method is mutually tied with local topology sequence The method of conjunction ensures the feasibility of disassembly sequence and its matching with regeneration scheme.First according to regeneration scheme, product structure With material toxicity etc., the parts of institute's dismounting in need are confirmed using multiple target backward induction method, form the minimum collection for dismantling part Close, so as to which partial disassembly's Sequence Planning problem to be converted into the complete Disassembly layout problem of minimum dismounting part set；Then lead to Cross traversal local topology figure and carry out the random feasible sequence created and meet dismounting dominance relation constraint.This method can not only generate can Capable global solution, while avoid complex precedence constraints reparation from operating, improve the convenience of genetic manipulation when evolution algorithm solves.
2. described real coding mechanism proposed by the present invention, each gene represents part in regeneration scheme individual Regeneration scheme, such as 1 represents material recycling, and 2 representatives remanufacture, and 3 represent directly recycling.Disassembly sequence individual uses n part Random dismounting weighted value represent, and be directly expressed as part sequence.This coded system not only dismantles part The sequence chromosome of middle length dynamic change becomes the chromosome of regular length, and to any evolutional operation of chromosome not Infeasible sequence can be produced.
3. improved Cooperative Evolutionary Algorithm proposed by the present invention, the algorithm is established in cooperation Symbiotic Evolutionary Algorithms and local friendship On the basis of mutual endosymbiosis evolution algorithm, using Local Interaction and endosymbiosis evolution strategy, elite solution enhanced search is added Strategy, and effectively avoid small range Local Interaction from being absorbed in precocity by global disruption and recovery, it is whole optimizing to realize global optimizing Under the target of body regeneration value, optimal dismantlement scheme and regeneration scheme are drawn, overcomes traditional target based on graph search method " multiple shot array " problem caused by component disassembly sequence planning strategy.
Brief description of the drawings：
Fig. 1 is the preferential figure of test product dismounting for being used to illustrate in the present invention.
Fig. 2 is the algorithm flow chart of present invention generation dismantlement scheme and regeneration scheme feasible solution.
Fig. 3 is the flow chart of the integer coding mechanism used in the present invention.
Fig. 4 is the dismantlement scheme of Complex Product dismounting regeneration and the Integrated Decision method stream of regeneration scheme of the present invention Cheng Tu.
Embodiment：
The present invention is further illustrated below in conjunction with the accompanying drawings.
The dismantlement scheme of Complex Product dismounting regeneration of the present invention and the Integrated Decision method of regeneration scheme, step is such as Under：
Step 1：The dismantlement scheme and regeneration scheme of the initial complicated product to be removed of random generation；
Step 2：According to complicated product component quality state to be removed and dismounting dominance relation, feasible dismounting is generated Scheme and regeneration scheme；
Step 3：Dismantlement scheme and regeneration scheme are encoded using real coding mechanism；
Step 4：Evolutional operation is carried out to above-mentioned coding using improved Cooperative Evolutionary Algorithm, optimizes overall regeneration value, Draw optimal dismantlement scheme and regeneration scheme；
Wherein the present invention sorts the method that is combined to ensure by proposing a kind of multiple target backward induction method with local topology The feasibility and dismantlement scheme of dismantlement scheme and the matching of regeneration scheme.
Feasible dismantlement scheme and regeneration scheme are wherein generated in step 2, is comprised the following steps that：
Step 1：The initial random regeneration scheme of generation and dismounting weight set；
Step 1.1：A regeneration scheme is randomly assigned to each part；
Step 1.2：Each part is distributed one 1 and uniquely dismantles weight as the part to unduplicated certificate n；
Step 2：Generate feasible regeneration scheme；
Step 2.1：The regeneration scheme of each part is checked, is revised as at random if program technology is infeasible feasible Regeneration scheme；
Step 2.2：When exist part be assigned to recycle when, if it is died of old age quality level be unsatisfactory for recycle minimum Quality level, then the part regeneration scheme is changed as recycling or is remanufactured；
Step 2.3：The regeneration rate of new regeneration scheme is checked, if regeneration rate is unsatisfactory for minimum threshold, randomly chooses one Individual regeneration scheme is the part of recycling, and its scheme is changed to remanufacture；
Step 2.4：If be still unsatisfactory for regenerate rate requirement, repeat step 2.3, otherwise, obtained one it is feasible Regeneration scheme, continue executing with step 3；
Step 3：By inversely traveling through the minimal set dismantled preferential figure and generate part to be torn open；
Step 3.1：The regeneration scheme of each part is traveled through, if the part will be remanufactured or recycled, by part Minimum dismounting set is added, if part contains poisonous and harmful substances, the part is equally added into minimum dismounting set, thus obtained initial Minimum dismounting set；
Step 3.2：The direct precursor set of each part, is to work as if there is a part in the minimum dismounting set of traversal The direct precursor of preceding traversal part, and the part is then also added into minimum dismounting set without minimum dismounting set is added, by This obtains the minimum dismounting set corresponding to regeneration scheme；
Step 4：Local topology figure corresponding to the minimum dismounting set of structure；
Step 4.1：Dismounting precedence relation matrix corresponding to the minimum dismounting set of generationIf all parts are all Need to dismantle, be then dismounting completely, directly perform step 5；Otherwise to any two part u, v in minimum dismounting set, if u It is v direct precursor, then makesOtherwise it is 0；
Step 4.2：A local topology figure PTG={ V, E } is built, wherein V is the vertex set for representing each part, E It is the side for representing removing relation；
Step 4.3：Calculate the I that becomes a mandarin of each node in local topology figureu, IuReflect total of part u direct precursors Number；
Step 5：Feasible disassembly sequence is generated based on dismounting weight and topological sorting method；
Step 5.1：Any one is without the part (I for directly dismantling forerunneru=0) can directly dismantle, search is current Demountable part node forms S in figuredIf the gesture of the set | Sd|=0, represent without dismountable part, computing Stop；If | Sd|=1, then the part is directly added into disassembly sequence set；If | Sd| ＞ 1, then according to dismounting weight to it In part carry out descending arrangement, and according to this by these parts add disassembly sequence；
Step 5.2：Delete and added in local topology figure PTG corresponding to the node and these parts of disassembly sequence set Side, update remaining node in PTG and become a mandarin；
Step 5.3：If local topology figure is not skyStep 5.1 is then repeated, otherwise stops computing, When having traveled through node all in local topology figure PTG, then a feasible dismantlement scheme has obtained, and then, obtain complete Feasible solution.
Real coding mechanism in step 3, each gene represents the regeneration scheme of a part in regeneration scheme individual, Such as 1 represents material recycling, and 2 representatives remanufacture, and 3 represent directly recycling.The random dismounting of n part of disassembly sequence individual Weighted value represents, and is directly expressed as part sequence.This coded system not only makes length dynamic in the dismounting of part The sequence chromosome of change becomes the chromosome of regular length, and can not all without generation to any evolutional operation of chromosome Capable sequence.
It is as follows the step of improved Cooperative Evolutionary Algorithm in step 4：
Step 1：Initialization of population, initialize regeneration scheme, i.e. randomizing scheme and random weight recombination；Check regeneration scheme Feasibility, and repair be feasible regeneration scheme；
Step 2：The initial fitness of individual is calculated respectively, to each feasible global solution, calculates its recycling profit, dismounting Cost and net profit, herein using net profit value as fitness evaluation value；
Step 3：Build the neighborhood of Local Interaction search；
Step 4：Symbiosis cooperation and competition operates, each individual selected in the neighborhood of another population one it is random Individual is used as symbiotic partner；Then, calculate each individual fitness (target function value) in the two neighborhoods and confirm current office Portion's adaptive optimal control degree, then evaluate each individual fitness and confirm local optimum fitness in the neighborhood；If greater than original Fitness, then substitute an inferior solution at random with the gene of optimal solution；
Step 5：Genetic evolution, individual in each neighborhood is selected, intersected and mutation operation produces new son individual, and Replace the poor individual in original seed group；
Step 6：Elite solution local strengthening is searched for；
Step 7：Evolve and stop judging, if having reached greatest iteration number, stop, otherwise repeat step 3；
Step 8：Global perturbation strategy, if the continuous g of locally optimal solutionBIn generation, does not update, then with certain probability to part Worst individual carries out disturbing operation and renewal, to increase the diversity of population, goes to and performs step 3.
Improved Cooperative Evolutionary Algorithm, the algorithm is established evolves in the endosymbiosis of cooperation Symbiotic Evolutionary Algorithms and Local Interaction On the basis of algorithm, using Local Interaction and endosymbiosis evolution strategy, elite solution enhanced search strategy is added, and pass through the overall situation Disruption and recovery effectively avoids small range Local Interaction from being absorbed in precocity, to realize global optimizing.
Described above is only the preferred embodiment of the present invention, it is noted that for the ordinary skill people of the art For member, some improvement can also be made under the premise without departing from the principles of the invention, and these improvement also should be regarded as the present invention's Protection domain.

Claims (4)

1. a kind of dismantlement scheme of Complex Product dismounting regeneration and the Integrated Decision method of regeneration scheme, it is characterised in that： Step is as follows
Step 1：The dismantlement scheme and regeneration scheme of the initial complicated product to be removed of random generation；
Step 2：According to complicated product component quality state to be removed and dismounting dominance relation, feasible dismantlement scheme is generated And regeneration scheme；
Step 3：Dismantlement scheme and regeneration scheme are encoded using real coding mechanism；
Step 4：Evolutional operation is carried out to above-mentioned coding using improved Cooperative Evolutionary Algorithm, optimizes overall regeneration value, simultaneously Draw optimal dismantlement scheme and regeneration scheme.
2. the dismantlement scheme of Complex Product dismounting regeneration as claimed in claim 1 and the Integrated Decision side of regeneration scheme Method, it is characterised in that：Feasible dismantlement scheme and regeneration scheme are generated in step 2, is comprised the following steps that：
Step 1：The initial random regeneration scheme of generation and dismounting weight set；
Step 1.1：A regeneration scheme is randomly assigned to each part；
Step 1.2：Each part is distributed one 1 and uniquely dismantles weight as the part to unduplicated certificate n；
Step 2：Generate feasible regeneration scheme；
Step 2.1：The regeneration scheme of each part is checked, feasible regeneration is revised as at random if program technology is infeasible Scheme；
Step 2.2：When exist part be assigned to recycle when, if it is died of old age quality level be unsatisfactory for recycle minimum mass Level, then the part regeneration scheme is changed as recycling or is remanufactured；
Step 2.3：The regeneration rate of new regeneration scheme is checked, if regeneration rate is unsatisfactory for minimum threshold, random selection one is again Raw scheme is the part of recycling, and its scheme is changed to remanufacture；
Step 2.4：If be still unsatisfactory for regenerate rate requirement, repeat step 2.3, otherwise, obtained one it is feasible again Raw scheme, continues executing with step 3；
Step 3：By inversely traveling through the minimal set dismantled preferential figure and generate part to be torn open；
Step 3.1：The regeneration scheme of each part is traveled through, if the part will be remanufactured or recycled, part is added Minimum dismounting set, if part contain poisonous and harmful substances, the part is equally added into minimum dismounting and gathered, thus obtain it is initial most Small dismounting set；
Step 3.2：The direct precursor set of each part, is current time if there is a part in the minimum dismounting set of traversal The direct precursor of part is gone through, and the part is then also added into minimum dismounting set without minimum dismounting set is added, thus To the minimum dismounting set corresponding to regeneration scheme；
Step 4：Local topology figure corresponding to the minimum dismounting set of structure；
Step 4.1：Dismounting precedence relation matrix corresponding to the minimum dismounting set of generationIf all parts are required for Dismounting, then it is dismounting completely, directly performs step 5；Otherwise to any two part u, v in minimum dismounting set, if u is v Direct precursor, then makeOtherwise it is 0；
Step 4.2：A local topology figure PTG={ V, E } is built, wherein V is the vertex set for representing each part, and E is generation The side of table removing relation；
Step 4.3：Calculate the I that becomes a mandarin of each node in local topology figureu, IuReflect the total number of part u direct precursors；
Step 5：Feasible disassembly sequence is generated based on dismounting weight and topological sorting method；
Step 5.1：Any one is without the part (I for directly dismantling forerunneru=0) can directly dismantle, searching for can in current figure S is formed with the part node of dismountingdIf the gesture of the set | Sd|=0, represent without dismountable part, computing to stop； If | Sd|=1, then the part is directly added into disassembly sequence set；If | Sd| ＞ 1, then according to dismounting weight to therein Part carries out descending arrangement, and these parts are added into disassembly sequence according to this；
Step 5.2：Delete in local topology figure PTG and added side corresponding to the node and these parts of disassembly sequence set, Remaining node becomes a mandarin in renewal PTG；
Step 5.3：If local topology figure is not skyStep 5.1 is then repeated, otherwise stops computing, works as traversal All nodes in local topology figure PTG, then feasible dismantlement scheme obtained, and then, obtain complete feasible solution.
3. the dismantlement scheme of Complex Product dismounting regeneration as claimed in claim 1 and the Integrated Decision side of regeneration scheme Method, it is characterised in that：Real coding mechanism in step 3, each gene represents the regeneration of a part in regeneration scheme individual Scheme, 1 represents material recycling, and 2 represent and remanufacture, and 3 represent and directly recycle, disassembly sequence individual the random of n part Weighted value is dismantled to represent.
4. the dismantlement scheme of Complex Product dismounting regeneration as claimed in claim 1 and the Integrated Decision side of regeneration scheme Method, it is characterised in that：It is as follows the step of improved Cooperative Evolutionary Algorithm in step 4：
Step 1：Initialization of population, regeneration scheme, i.e. randomizing scheme and random weight recombination are initialized, check regeneration scheme can Row, and it is feasible regeneration scheme to repair；
Step 2：The initial fitness of individual is calculated respectively, to each feasible global solution, calculates its recycling profit, disassembly cost And net profit, herein using net profit value as fitness evaluation value；
Step 3：Build the neighborhood of Local Interaction search；
Step 4：Symbiosis cooperation and competition operates, and each individual selects a random individual in the neighborhood of another population As symbiotic partner；Then, calculate each individual fitness i.e. target function value in the two neighborhoods and confirm current part most Excellent fitness, then evaluate each individual fitness and confirm local optimum fitness in the neighborhood；If greater than original suitable Response, then an inferior solution is substituted at random with the gene of optimal solution；
Step 5：Genetic evolution, individual in each neighborhood is selected, intersected and mutation operation produces new son individual, and replaced Fall the poor individual in original seed group；
Step 6：Elite solution local strengthening is searched for；
Step 7：Evolve and stop judging, if having reached greatest iteration number, stop, otherwise repeat step 3；
Step 8：Global perturbation strategy, if the continuous g of locally optimal solutionBIn generation, does not update, then inferior to part individual with certain probability Body carries out disturbing operation and renewal, to increase the diversity of population, goes to and performs step 3.
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